Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.

Who you are

We are looking for a highly motivated and analytical Data Scientist to join our growing data team. You will play a key role in extracting insights from large datasets, building predictive models, and supporting data-driven decision-making across departments.

What you'll do

• Collect, process, and analyze large datasets from multiple sources
• Build and deploy machine learning models to solve business problems
• Design and implement A/B tests and statistical analyses
• Collaborate with cross-functional teams (product, engineering, marketing) to define analytics requirements
• Communicate complex data insights in a clear and actionable manner to stakeholders
• Develop dashboards and visualizations to monitor key metrics
• Stay current with the latest trends and technologies in data science and AI

What we're looking for

• Bachelor’s and or Master’s degree in Computer Science, Mathematics, Statistics, or related field
• 4+ years of proven experience as a Data Scientist or Data Analyst
• Strong knowledge of Python/R and SQL
• Hands-on experience with machine learning frameworks (e.g., scikit learn, tensroflow, pytorch)
• Experience with big data tools (e.g., Spark, Hadoop)
• Familiarity with data visualization tools
• Strong analytical, problem-solving, and communication skills

While not required, these are a plus:

• Experience with cloud platforms preferably AWS (S3, Sagemaker, Airflow etc)
• Strong SQL skills, with experience in Snowflake, MySQL, and PostgreSQL
• Familiarity with data visualization tools (e.g., Tableau, Power BI, Looker)

3 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection.

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. #LI-SR1 #LI-Onsite

Who we are

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.

Who you are

As a Senior Data Engineer at Metropolis, you will play a key role in shaping both customer-facing and business-facing data products that align with our mission. Your technical expertise and analytical acumen will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. Join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

What you'll do

• Collaborate with engineers, product managers, and data scientists to understand data needs, and develop end-to-end data pipelines, solutions, and foundational data sets
• Design and own the data architecture for large-scale projects, making informed decisions about design and operational trade-offs
• Build, launch, and optimize sophisticated data pipelines, data models, and visualizations that support diverse use cases across multiple products or domains
• Define and manage Service Level Agreements (SLAs) for all data sets within areas of ownership
• Implement data security models based on privacy requirements, ensure compliance with safeguards, address data quality issues, and evolve data governance processes
• Solve complex data integration challenges using optimal ETL/ELT patterns, frameworks, and query techniques for both structured and unstructured data sources
• Maintain and enhance existing production processes by optimizing complex code using advanced algorithmic concepts 
• Optimize pipelines, dashboards, frameworks, and systems to streamline data artifact development
• Mentor team members, providing and receiving actionable feedback to foster skill growth and collaboration
• Ensure flexibility with availability during evening hours

What we're looking for

• Bachelor's degree in computer science, Computer Engineering, or a relevant technical field; a master's degree is preferred
• 5+ years of experience in data engineering, database engineering, business intelligence, data warehousing, and ETL tools, working with large data sets in the cloud
• Proficiency in SQL, ETL/ELT, and data modeling, with extensive experience in Snowflake and dbt 
• 5+ years of experience with Python, and experience building scalable Big Data solutions and ETL ecosystems
• Hands-on experience with RDBMS such as MySQL, MS SQL Server, and Postgres
• Familiarity with integration tools like Airflow and Automic, along with a working knowledge of CI/CD pipelines
• Ability to deliver high standards of code quality, system reliability, and performance
• Experience with Spark and PySpark to handle large-scale data processing and enhance data pipeline efficiency
• Strong proficiency in Terraform is a must-have.

Our Stack

• Languages + Frameworks: TypeScript, React, Scala (principally), Java (limited)
• Datastores: MySQL, PostgreSQL, Snowflake
• Cloud: AWS
• Version control: Git & GitHub
• AI Tooling: Copilot on GitHub
• Observability: Datadog

When you join Metropolis, you’ll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. #LI-SR1 #LI-Onsite

Zeta Marketing Platform (ZMP) is a machine learning/AI powered customer acquisition and CRM multi-tenant platform. The backend developer will work on server-side APIs and services that enable a highly distributed event pipeline and a stack that gets tens of thousands of messages per second.

As a senior member of the Software Engineering team, you will join the group responsible for designing, developing, and owning the distributed systems CRI 1 platform for Zeta. You will collaborate with your fellow Engineers and Product managers to develop a roadmap and subsequent projects to build the next generation comprehensive, multichannel marketing solution that unifies and unlocks data across digital touch points, driving return on marketing investment.

You should have a deep knowledge of distributed systems and cloud architecture. You will need extensive design and development experience and be passionate about working with high-throughput systems where the issues of throughput, performance, redundancy, and concurrency are paramount.

 Key Responsibilities:

 As a Senior Software Developer, you will be:

• Responsible for independently and cooperatively understanding business requirements, designing, and implementing core components for real-world marketing automation platform.
• Designing, implementing application code to satisfy product requirements
• Ensuring high product quality through rigorous code reviews and unit tests
• Fixing bugs and implementing enhancements
• Taking ownership of a significant product component in design and implementation

Requirements:

• We are looking for exceptional talent with superior academic credentials and a solid foundation in computer sciences and distributed systems design and development.
• The candidate will have at least 4 years of experience developing scalable, robust sohware platforms using Java/Ruby/Python or an equivalent language.
• An undergraduate degree in Computer Science (or a related field) from a university where the primary language of instruction is English is strongly desired.
• Strong communication skills in a large-distributed development team environment are essential.
• Experience in Advertising Attribution domain is a plus

Requirements:

• BS or MS in Computer Science or related field
• 4 - 8 years of working experience with J2EE technology, Python or equivalent OO paradigm
• Strong knowledge and experience with Kafka, Elastic Search, Airflow, NoSQL databases such as Aerospike,Thrift, Cl, and AWS.
• Experience with SQL languages
• Experience working with container-based solutions is a plus.
• Experience working in a fast-paced technology environment.
• Strong object-oriented programming and design skills.
• Excellent problem solving, critical thinking, and communication skills.
• Ability and desire to learn new skills and take on new tasks.

 Company Profile:

Zeta Global is a NYSE listed data-powered marketing technology company with a heritage of innovation and industry leadership. Founded in 2007 by entrepreneur David A. Steinberg and John Sculley, former CEO of Apple Inc and Pepsi-Cola, the Company combines the industry’s 3rd largest proprietary data set (2.4B+ identities) with Artificial Intelligence to unlock consumer intent, personalize experiences and help our clients drive business growth.

Our technology runs on the Zeta Marketing Platform, which powers ‘end to end’ marketing programs for some of the world’s leading brands. With expertise encompassing all digital marketing channels – Email, Display, Social, Search and Mobile – Zeta orchestrates acquisition and engagement programs that deliver results that are scalable, repeatable and sustainable.

Zeta Global is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, gender, ancestry, color, religion, sex, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

Zeta Global Recognized in Enterprise Marketing Software and Cross-Channel Campaign Management Reports by Independent Research Firm

https://www.forbes.com/sites/shelleykohan/2024/06/19/amazon-partners-with-zeta-global-to-deliver-gen-ai-marketing-automation/

https://www.cnbc.com/video/2024/05/06/zeta-global-ceo-david-steinberg-talks-ai-in-focus-at-milken-conference.html

https://www.businesswire.com/news/home/20240904622808/en/Zeta-Increases-3Q%E2%80%9924-Guidance

https://www.prnewswire.com/news-releases/zeta-global-opens-ai--data-labs-in-san-francisco-and-nyc-300945353.html

https://www.prnewswire.com/news-releases/zeta-global-recognized-in-enterprise-marketing-software-and-cross-channel-campaign-management-reports-by-independent-research-firm-300938241.html

We invite you to explore this opportunity to be a part of the Zeta family……

Should you need any assistance or require further information, please do not hesitate to contact us.

What we want to accomplish and why we need you.

Suki is a leading technology company that provides AI voice solutions for healthcare. Its mission is to reimagine the healthcare technology stack, making it invisible and assistive to lift the administrative burden from clinicians. Its flagship product is Suki Assistant, an AI assistant that uses generative AI to automatically create clinical documentation by ambiently listening to patient-clinician conversations. Suki helps clinicians complete notes 72% faster on average, assists with other tasks including coding and answering questions, and generates incremental revenue for organizations, delivering a 9X ROI in year 1. Suki also offers its proprietary AI and speech platform, Suki Platform, to partners who want to create best-in-class ambient and voice experiences for their solutions. Clinicians that use Suki already spend over 70% less time on administrative tasks, and we’re striving to do even better. Come and join us! 

We are a user-driven company and are committed to making sure every pixel of our product is in service of the doctors. We’re a team of technologists, clinicians, and industry experts working together to push the limits on technology used in medicine. We’re confident enough to move fast and talented enough not to break things.

What will you do every day?

We are looking for a Software Architect  to join our Engineering team. Suki's architecture practice is at an inflection point. We have sustained significant CCU growth, completed a demanding OLTP Database scaling journey, leveraged Redis Streams based service orchestration, deployed self-hosted ML models, built agent-driven workflows, launched an Offline Data Platform, and maintained a client surface spanning iOS, Android, Web, SDKs, and a Chrome extension — with on-device ML capabilities across all of them.

The Architect is the person who holds institutional memory and architectural coherence across this surface area — so that decisions made in isolation don't quietly contradict each other, patterns are reused rather than reinvented, and deviations from established patterns are documented, not silently absorbed. The work ahead includes enhanced agentic capabilities, continued multi-region expansion, investments on stream-based/offline data processing, and a growing ML inference footprint.

On a day to day basis, you will: 

• Maintain architectural coherence across a complex and wide surface area. 
• Own the load-bearing substrate through future growth and failure scenarios. The system must survive several multiples of current enterprise scale and every class of infrastructure event we can name.
• Drive the structural decomposition of platform and domain boundaries, service boundaries across the microservice portfolio, agentic framework direction, auth and access-control architecture, and cross-cutting concerns like observability and rate limiting.
• Bridge AI research and production infrastructure. Translate LLM and model requirements into efficient, production-grade services. Lead the agentic framework direction — memory architectures, tool orchestration, A2A patterns, semantic caching. Operate a GPU fleet at high duty cycle and understand dynamic batching, cross-session batching tradeoffs, and HPA calibration for GPU workloads.
• Document architectural patterns and deviations. Write Architectural Design Records, RFCs, and breaking-points documents that stand alone for readers unfamiliar with the context. Document deviations from established patterns with their reasons — not as failures, but as data points. 
• Remain hands-on — stay connected to the craft, read and write code. Prototype new architectures. Review pull requests for patterns that matter. Implement the hard parts of a new pattern yourself when it matters. Lead resolution of the most critical incidents. 
• Mentor and elevate the engineering organization. Act as a technical multiplier for senior engineers across backend, data, and ML disciplines. Hold a room, defend a position under pushback without collapsing into agreement, and adjust register for engineering vs. product vs. leadership audiences. Foster a culture of deep technical understanding, not just pattern-matching.
• Represent Suki’s architecture and engineering both in internal and external forums through technical blogs, conferences and meetups

QUALIFICATIONS 

• Bachelor's or Master's degree in Computer Science or a related field, or equivalent production experience 
• 10+ years of professional software engineering experience, with a proven track record operating at an Architect, Staff, or Principal level 
• Expert-level proficiency in Go or Python, with the ability to lead architectural decisions and remain hands-on in code 
• Production ownership of a real-time streaming system (Redis Streams, Kafka, Pulsar, or equivalent) at scale — including personal pager experience and a specific debugging story for a duplicate-processing or lost-message bug 
• Experience operating multi-TB storage systems with active OLTP traffic 
• Hands-on experience with offline/batch architectures: Airflow or equivalent orchestration, columnar formats (Iceberg, Delta, or Hudi), and warehouse-scale query engines (BigQuery, Snowflake, or Redshift) 
• Experience designing and operating GPU inference infrastructure at scale, including dynamic batching, Triton/TensorRT, and HPA calibration for GPU workloads — or equivalent ML inference platform depth 
• Experience integrating and scaling systems using LLM APIs or foundation models, with opinions about agent framework design, memory architectures, and tool orchestration 
• Demonstrated experience navigating product-vs-platform decomposition in a real organization — including having been wrong, and articulating what the reversing signal was
• Proven ability to reason about client-side implications of backend decisions across native mobile, web, SDK, and browser extension surfaces 
• Familiarity with healthcare-adjacent regulation (HIPAA, PIPEDA, PHIPA, SOC2, or HITRUST) as a design constraint, not just a compliance requirement, will be a strong plus 
• Strong experience with GCP, Kubernetes, Docker, gRPC, and Protocol Buffers; multi-region architecture and data residency design will be a strong plus 

What We're Looking For

• Distinguished Technical Expertise: You are a recognized expert with a proven history of architecting, building, and operating complex systems with a strong software engineering talent.
• Strategic, Systems-Level Thinker: You look beyond immediate requirements to anticipate future challenges. You can navigate deep ambiguity, identify long-term risks, and make high-judgment decisions that balance technical purity with business velocity.
• Pragmatic and Action-Oriented: You have a bias for action and a data-driven approach to problem-solving. You understand the entire lifecycle of an ML-powered feature, from data to deployment, and know how to ship robust solutions quickly.
• Leadership Through Influence: You have a demonstrated ability to lead complex, cross-functional technical initiatives without direct authority. You build 

Tell me more about Suki

• On a roll: Named by Fast Company as one of the most innovative companies, named Google’s Partner of the Year for AI/ML, named by Forbes as one of the top 50 companies in AI .
• Great team: Founded, managed, and backed by successful tech veterans from Google and Apple and medical leaders from UCSF and Stanford. We have technologists and doctors working side-by-side to solve complex problems.
• Great investors: We’re backed by Venrock, First Round Capital, Flare Capital, March Capital, Hedosophia and others. With our $165M raised so far, we have the resources to scale.
• Huge market: Disrupting a massive, growing $30+ billion market for transcription, dictation, and order-entry solutions. Our vision is to become the voice user interface for healthcare, relieving the administrative burden on doctors instead of adding to it.
• Great customers: Our solutions are used in health systems and clinics across the country, supporting clinicians across dozens of specialties.  Check out what one of our users says about how Suki has helped his practice.
• Impact: You’ll make an impact from day one. You’ll join a team working towards a shared purpose with a culture built upon deep empathy for doctors and passion for making their lives better. 

Suki is an Equal Opportunity Employer. We are dedicated to building a company that fosters inclusion and belonging and reflects the diverse communities we serve across the country. We know we are stronger this way, and we look forward to growing our team with these shared values.

Company Introduction

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been at since our inception. We are all entrepreneurial surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional trade-offs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

Rocket Growth (RG) is Coupang’s fulfilment business that empowers sellers to provide customers with best-in-class delivery and post-purchase experiences.

As one of Coupang’s fastest-growing teams, RG has an ambitious roadmap of innovative products and features. We are looking for driven individuals who thrive on solving complex problems and collaborating with talented peers to shape the future of e-commerce.

A Staff Data Analyst works on projects related to the quality, availability, and depth of data needed by Coupang to make business decisions. This person will use their deep expertise in SQL, data ETL development, and data integrity to ensure that necessary information is available for all levels of analysis at Coupang. Additionally, this person will contribute to analytics projects designed to help drive Coupang's growth, support specific initiatives from Growth Marketing and other business units, and help less senior data analysts with their development.

What You Will Do

• Leads projects related to the quality, availability, and depth of data needed by Coupang to make business decisions. 
• Use their deep expertise in SQL, data ETL development, and data integrity to ensure that necessary information is available for all levels of analysis at Coupang. 
• Contribute to analytics projects designed to help drive Coupang's growth, support specific initiatives from Growth Marketing and other business units, and help senior data analysts with their development.
• Own and drive critical decision-making across a range of ambiguous business problems using data.
• Structure and analyze large datasets, define constraints and parameters, and develop decision models.
• Run simulations and optimization analyses to improve business outcomes and support strategic decisions.
• Challenge existing processes and propose data-backed improvements.
• Translate insights into actionable recommendations and influence stakeholders across functions.
• Collaborate with diverse teams to align on goals and deliver impactful solutions.

 Basic Qualifications:  

• 8+ years of relevant working experience in a data analytics role
• Proficiency in Excel, SQL and Python/R for data extraction, manipulation and analysis
• Strong knowledge of data visualization (PowerBI, Tableau or other tools) and data storytelling to communicate insights effectively to non-experts
• Business-level fluency in English

Preferred Qualifications:

• Experience with data engineering tools such as GitHub and Airflow
• Strong knowledge of statistics, ML techniques
• Previous experience in e-commerce, logistics, or AdTech companies

Type of work model

Hybrid

Our Hybrid work model: Coupang hybrid work model is designed to enable a culture of collaboration that acts a catalyst to enrich the experience of employees. Employees are required to work at least 3 days in the office per week, with the flexibility to work from home 2 days a week, depending on the role requirement. Some businesses may require more time in office due to nature of work.  

Details to consider 

Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.  

Privacy Notice 

Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/  

Company Introduction

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been at since our inception. We are all entrepreneurial surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional trade-offs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.

Role Overview

Rocket Growth (RG) is Coupang’s fulfilment business that empowers sellers to provide customers with best-in-class delivery and post-purchase experiences.

As one of Coupang’s fastest-growing teams, RG has an ambitious roadmap of innovative products and features. We are looking for driven individuals who thrive on solving complex problems and collaborating with talented peers to shape the future of e-commerce.

A Staff Data Analyst works on projects related to the quality, availability, and depth of data needed by Coupang to make business decisions. This person will use their deep expertise in SQL, data ETL development, and data integrity to ensure that necessary information is available for all levels of analysis at Coupang. Additionally, this person will contribute to analytics projects designed to help drive Coupang's growth, support specific initiatives from Growth Marketing and other business units, and help less senior data analysts with their development.

What You Will Do

• Leads projects related to the quality, availability, and depth of data needed by Coupang to make business decisions. 
• Use their deep expertise in SQL, data ETL development, and data integrity to ensure that necessary information is available for all levels of analysis at Coupang. 
• Contribute to analytics projects designed to help drive Coupang's growth, support specific initiatives from Growth Marketing and other business units, and help senior data analysts with their development.
• Own and drive critical decision-making across a range of ambiguous business problems using data.
• Structure and analyze large datasets, define constraints and parameters, and develop decision models.
• Run simulations and optimization analyses to improve business outcomes and support strategic decisions.
• Challenge existing processes and propose data-backed improvements.
• Translate insights into actionable recommendations and influence stakeholders across functions.
• Collaborate with diverse teams to align on goals and deliver impactful solutions.

 Basic Qualifications:  

• 8+ years of relevant working experience in a data analytics role
• Proficiency in Excel, SQL and Python/R for data extraction, manipulation and analysis
• Strong knowledge of data visualization (PowerBI, Tableau or other tools) and data storytelling to communicate insights effectively to non-experts
• Business-level fluency in English

Preferred Qualifications:

• Experience with data engineering tools such as GitHub and Airflow
• Strong knowledge of statistics, ML techniques
• Previous experience in e-commerce, logistics, or AdTech companies

Type of work model

Hybrid

Our Hybrid work model: Coupang hybrid work model is designed to enable a culture of collaboration that acts a catalyst to enrich the experience of employees. Employees are required to work at least 3 days in the office per week, with the flexibility to work from home 2 days a week, depending on the role requirement. Some businesses may require more time in office due to nature of work.  

Details to consider 

Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.  

Privacy Notice 

Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below: https://www.coupang.jobs/privacy-policy/  

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 12–15+ years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

• Documentation and teaching: you make complex systems understandable; you uplevel teams. 

 Please complete the attached Internal Transfer Request Form and submit.   

Please make sure to apply with your Coupang e-mail address.   

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview 

The Taiwan Data, Analytics & AI team is the engine driving Coupang’s rapid expansion in the Taiwan market. Our mission is to transform massive datasets into actionable intelligence and automated systems that power business decisions. As we scale, we are transitioning from foundational growth to a sophisticated enterprise AI ecosystem. We are building the next generation of data services that ensure every stakeholder across the Taiwan organization has access to high-integrity, automated, and intelligent insights.

As a Staff Machine Learning Engineer, you will be a technical leader responsible for the architecture and automation of our regional data intelligence layer. Your primary focus will be bridging the gap between raw data and organizational knowledge. You will lead the automation of our Knowledge Base, govern the integrity of our core metrics, and scale our analytics services to support the entire Taiwan organization.

This is a high-impact role where technology meet business, and you will design systems that not only provide data but ensure that the "truth" behind the data is refreshed, accurate, and easily accessible through AI-driven interfaces and help us become true AI first Analytics Organisation.

What You Will Do

• Automated Knowledge Engineering: Design and implement end-to-end ML pipelines to automate the creation and maintenance of a centralized Knowledge Base, utilizing LLMs and RAG (Retrieval-Augmented Generation) to synthesize complex business logic.

• Metric Integrity & Governance: Develop systemic checks and automated validation frameworks to ensure the integrity of business metrics. You will be the architect of a "Single Source of Truth," ensuring definitions remain consistent across all AI and reporting services.

• AI-Driven Pipeline Automation: Architect "Self-Healing" data pipelines using AI tools to automate schema mapping, error detection, and recovery. Implement LLM-powered agents to generate, optimize, and document ETL code, reducing manual engineering overhead.

• Scalable AI Services: Architect and scale existing Data and Analytics services to handle the increasing demands of the entire Taiwan organization, ensuring high availability and low-latency access to insights.

• Feedback & Refresh Loops: Build automated feedback mechanisms to identify "stale" content or drifting metric definitions. You will design the workflows that ensure both new and existing knowledge content is refreshed regularly based on user behavior and data shifts.

• Systemic Optimization: Drive innovation in semantic retrieval and query understanding to allow non-technical stakeholders to interact with complex data layers using natural language.

• Enablement & Training: Act as a force multiplier by enabling and training various reporting functions (Finance, Ops, Marketing). You will create the tools and frameworks that allow these teams to self-serve with high confidence.

• Technical Mentorship: Lead by example in code quality, system design, and experimentation. Mentor senior and mid-level engineers, fostering a culture of technical excellence and continuous improvement.

Basic Qualifications

•  Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field.

• 8+ years of professional experience in software engineering and applied machine learning (with at least 2 years in a Staff or Lead capacity).

• Proficiency in Python or Java, with deep experience building production-grade ML systems and scalable data pipelines.

• Strong experience with SQL and big data technologies (e.g., Spark, Presto/Trino, Airflow).

Preferred Qualifications

• Advanced Degree: Master’s or PhD in a relevant technical field.

• AI/LLM Expertise: Proven track record of deploying Large Language Models (LLMs), vector databases, and embedding-based retrieval systems in a production environment.

• Automated Management: Experience with AI-powered data management tools (e.g., automated data profiling, AI-driven data catalogs, or LLM-assisted SQL generation).

• Enterprise Scaling: Experience transitioning data organizations from "growth-phase" scripts to "enterprise-phase" robust microservices.

• Cloud Proficiency: Hands-on experience with AWS or GCP (SageMaker, Vertex AI, BigQuery).

• MLOps Mastery: Experience with ML lifecycle tools like MLflow, Kubeflow, or Weights & Biases to manage model lineage and data drift.

• Communication: Exceptional ability to communicate technical roadmaps to non-technical business leaders and influence cross-functional stakeholders in a fast-paced, global environment.

Type of work model 

• Hybrid 

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview 

The Taiwan Data, Analytics & AI team is the engine driving Coupang’s rapid expansion in the Taiwan market. Our mission is to transform massive datasets into actionable intelligence and automated systems that power business decisions. As we scale, we are transitioning from foundational growth to a sophisticated enterprise AI ecosystem. We are building the next generation of data services that ensure every stakeholder across the Taiwan organization has access to high-integrity, automated, and intelligent insights.

As a Staff Machine Learning Engineer, you will be a technical leader responsible for the architecture and automation of our regional data intelligence layer. Your primary focus will be bridging the gap between raw data and organizational knowledge. You will lead the automation of our Knowledge Base, govern the integrity of our core metrics, and scale our analytics services to support the entire Taiwan organization.

This is a high-impact role where technology meet business, and you will design systems that not only provide data but ensure that the "truth" behind the data is refreshed, accurate, and easily accessible through AI-driven interfaces and help us become true AI first Analytics Organisation.

What You Will Do

• Automated Knowledge Engineering: Design and implement end-to-end ML pipelines to automate the creation and maintenance of a centralized Knowledge Base, utilizing LLMs and RAG (Retrieval-Augmented Generation) to synthesize complex business logic.

• Metric Integrity & Governance: Develop systemic checks and automated validation frameworks to ensure the integrity of business metrics. You will be the architect of a "Single Source of Truth," ensuring definitions remain consistent across all AI and reporting services.

• AI-Driven Pipeline Automation: Architect "Self-Healing" data pipelines using AI tools to automate schema mapping, error detection, and recovery. Implement LLM-powered agents to generate, optimize, and document ETL code, reducing manual engineering overhead.

• Scalable AI Services: Architect and scale existing Data and Analytics services to handle the increasing demands of the entire Taiwan organization, ensuring high availability and low-latency access to insights.

• Feedback & Refresh Loops: Build automated feedback mechanisms to identify "stale" content or drifting metric definitions. You will design the workflows that ensure both new and existing knowledge content is refreshed regularly based on user behavior and data shifts.

• Systemic Optimization: Drive innovation in semantic retrieval and query understanding to allow non-technical stakeholders to interact with complex data layers using natural language.

• Enablement & Training: Act as a force multiplier by enabling and training various reporting functions (Finance, Ops, Marketing). You will create the tools and frameworks that allow these teams to self-serve with high confidence.

• Technical Mentorship: Lead by example in code quality, system design, and experimentation. Mentor senior and mid-level engineers, fostering a culture of technical excellence and continuous improvement.

Basic Qualifications

•  Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related technical field.

• 8+ years of professional experience in software engineering and applied machine learning (with at least 2 years in a Staff or Lead capacity).

• Proficiency in Python or Java, with deep experience building production-grade ML systems and scalable data pipelines.

• Strong experience with SQL and big data technologies (e.g., Spark, Presto/Trino, Airflow).

Preferred Qualifications

• Advanced Degree: Master’s or PhD in a relevant technical field.

• AI/LLM Expertise: Proven track record of deploying Large Language Models (LLMs), vector databases, and embedding-based retrieval systems in a production environment.

• Automated Management: Experience with AI-powered data management tools (e.g., automated data profiling, AI-driven data catalogs, or LLM-assisted SQL generation).

• Enterprise Scaling: Experience transitioning data organizations from "growth-phase" scripts to "enterprise-phase" robust microservices.

• Cloud Proficiency: Hands-on experience with AWS or GCP (SageMaker, Vertex AI, BigQuery).

• MLOps Mastery: Experience with ML lifecycle tools like MLflow, Kubeflow, or Weights & Biases to manage model lineage and data drift.

• Communication: Exceptional ability to communicate technical roadmaps to non-technical business leaders and influence cross-functional stakeholders in a fast-paced, global environment.

Type of work model 

• Hybrid 

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

About Okta

At Okta, our mission is to enable any organization to use any technology, making the world a more secure and connected place. We are the leading independent provider of identity for the enterprise. We work with an incredible array of customers, from the largest enterprises to the most innovative startups, to help them securely connect their people to technology. As we enter a new phase of growth, our AI and data capabilities will be a critical pillar of our success, powering secure and scalable products that serve both our customers and employees.

The Opportunity

Okta is seeking a Principal Data Engineer to be the technical visionary for our internal data platform that supports our internal AI use cases with AI ready data. Reporting to the Sr Manager of Enterprise Data Platform, this role is responsible for turning the data product vision into a secure, scalable, and elegant technical reality. You will own the "how"—the technical strategy, implementation, and scalability that brings our AI and data product roadmap to life.

This role requires a technical leader who can balance today’s execution with building a durable foundation for the future. You will own the technical standards for engineering excellence, security, and governance, ensuring our core data platform is trusted and ready to power the next generation of AI-powered products and decision-making at Okta.

What You’ll Do

• Own the technical strategy and implementation for the company's AI data platform, translating product requirements into a concrete technical vision centered on Snowflake, AWS, dbt.
• Design and implement a robust security and governance framework as a core pillar of the platform, ensuring our high-compliance, high-security standards are met.
• Build automated solutions for data classification, access control, and vulnerability management (Nessus/Qualys), ensuring data is secure and trusted for AI consumption.
• Implement and manage the strategy for infrastructure as code (Terraform) and CI/CD (GitHub/GitLab) to ensure secure, reproducible, and auditable deployments.
• Set the bar for engineering excellence, driving best practices in code quality, system design, and operational readiness.
• Serve as an engineering partner to the Principal Product Manager, providing technical feasibility, scoping, and architectural guidance.
• Communicate technical vision, strategy, and trade-offs clearly to senior leadership and cross-functional teams.
• Collaborate with the AI, security, and analytics teams to ensure the data platform meets the complex needs of the entire business.

What You Bring

• Experience: 10+ years of data engineering experience, with at least 5 years focused on architecting data platforms for data products, analytics, and/or AI-driven products. Experience with high-compliance/high-security regulated environments is a plus.
• Technical Authority: Deep and recognized mastery of data platforms and architecture, including cloud applications like Snowflake, Databricks, and AWS. Expert-level understanding of data pipeline and orchestration tools like dbt, Airflow, Fivetran, and Terraform.
• Security & Governance DNA: Deep expertise in designing and implementing technical frameworks for data governance, access control, and security within a modern data stack.
• Cross-Functional Partnership: A proven track record of partnering successfully with product management and business leaders to translate vision into high-impact technical solutions.
• Balance of Today vs. Tomorrow: Ability to deliver immediate, high-quality engineering solutions while building a scalable and maintainable foundation for future innovation.

What Success Looks Like

• A secure, scalable, and elegantly designed AI data platform that serves as the trusted data foundation for the company.
• Robust, automated data governance and security frameworks embedded into the platform's core architecture.
• A well-architected and cost-optimized tech stack that accelerates development and reduces operational friction.
• Elevated technical capabilities and engineering excellence across the team, driven by your mentorship and leadership.

#LI_Hybrid 

P24713_3369501

About Okta

At Okta, our mission is to enable any organization to use any technology, making the world a more secure and connected place. We are the leading independent provider of identity for the enterprise. We work with an incredible array of customers, from the largest enterprises to the most innovative startups, to help them securely connect their people to technology. As we enter a new phase of growth, our AI and data capabilities will be a critical pillar of our success, powering secure and scalable products that serve both our customers and employees.

The Opportunity

Okta is seeking a Senior Data Engineer to join our Enterprise Data Platform team. Reporting to the Sr. Manager of Enterprise Data Platform, you will be a key hands-on contributor responsible for building the data platform that supports our internal AI use cases with AI-ready data. You will help turn the data product vision into a secure, scalable, and elegant technical reality by developing and implementing core components of our data infrastructure.

This role requires a skilled engineer who is passionate about building high-quality data solutions. You will contribute to the team’s standards for engineering excellence and help ensure our core data platform is trusted and ready to power AI-powered decision-making at Okta.

What You’ll Do

• Build and maintain performant data pipelines and data models on the company's AI data platform, using Snowflake, AWS, and dbt.
• Implement components of our security and governance framework to ensure high-compliance and security standards are met.
• Develop automated solutions for data classification, access control, and contribute to our vulnerability management processes.
• Use infrastructure as code (Terraform) and CI/CD (GitHub/GitLab) to build, test, and deploy data infrastructure securely and reliably.
• Adhere to and champion best practices in code quality, system design, and operational readiness.
• Collaborate closely with product managers, senior engineers, and analytics teams to deliver high-quality data solutions that meet business needs.

What You Bring

• Experience: 5+ years of data engineering experience, with a focus on building data pipelines, data models, and working on data platforms. 
• Technical Proficiency: Strong, hands-on experience with cloud data platforms (Snowflake, Databricks, or similar) and AWS. Solid understanding of data pipeline and orchestration tools like dbt, Airflow, or Fivetran, and IaC with Terraform.
• Security & Governance Mindset: Experience implementing security controls, and a good understanding of data governance principles within a modern data stack.
• Collaborative Spirit: A proven track record of working effectively in a team environment with product managers, analysts, and other engineers to deliver features.
• Problem Solver: Ability to tackle well-defined technical problems and deliver high-quality, maintainable engineering solutions.

What Success Looks Like

• You are consistently delivering high-quality, reliable, and well-tested data pipelines and platform features.
• The infrastructure you build is automated, secure, and aligns with the team’s best practices.
• You are a trusted, collaborative, and productive member of the data engineering team.
• Your work directly contributes to a cost-optimized and efficient tech stack that accelerates development for your peers.

#LI_Hybrid 

P24719_3369503

Auth0 is an easy-to-implement, authentication and authorization platform designed by developers for developers. We make applications’ login boxes safe, secure, and seamless for anyone logging in.

The Auth0 Data Engineering Team

Within Auth0, the Data Engineering team builds solutions to support analytics needs for the whole organization and is in charge of the Data Platform. It is divided into 3 groups:

• Pipeline team, sitting closer to the Platform team and data producers and in charge of the efficient data ingestion and provision of quick access to unmodeled data
• Warehouse team sitting closer to the business teams and data consumers and in charge of modeling the data in the data warehouse to abstract away the complexity for data consumers, simplifying the organization’s analysis, reporting and decision-making
• Interface team responsible for creating and managing connections between the data platform and various external systems (internal or external facing), making sure everyone has access to consistent and reliable data

The Senior Data Engineer Opportunity

Reporting to the manager of the Data Engineering Pipeline team, the senior data engineer will be a key player in ensuring the reliability and efficiency of our core data platform. This role is crucial, providing the stable data foundation that not only 'runs the business' day-to-day but also directly empowers the organization to unlock growth and build innovative new products. We are looking for an autonomous and proactive engineer who can take ownership of our data ingestion pipelines, work closely with platform teams and data producers, and onboard new data from various internal and external systems. You will be part of a team creating robust, scalable data solutions using a modern, best-in-class toolset.

What you’ll be doing 

• Own and operate our critical data pipelines and infrastructure, participating in the team's support rotation to ensure high availability and business continuity.
• Lead troubleshooting efforts to fix complex pipeline or infrastructure issues, demonstrating a willingness to go beyond the direct scope of the team to find resolutions.
• Manage the data onboarding lifecycle, working with stakeholders to integrate new internal and external data sources into our platform using our suite of tools.
• Develop and deploy robust, scalable data solutions using modern tools and technologies like Snowflake, dbt, Airflow, and Terraform.
• Continuously learn and advocate for modern technologies and best practices to improve data delivery and engineering efficiency.

What you’ll bring to the role

• 5+ years of software development experience, with at least 3+ years working on large-scale data systems.
• Strong proficiency in SQL for data manipulation and Python for data pipeline development.
• Hands-on experience building and operating data pipelines in a cloud environment (AWS preferred).
• Hands-on experience with the modern data stack, specifically:
• Data Warehousing: Snowflake
• Data Transformation: dbt
• Infrastructure as Code: Terraform
• Experience with data ingestion, streaming, and event-driven architecture (e.g., Kafka, CDC, Snowpipe).
• Knowledge of data security and data privacy best practices
• A strong understanding of data modeling principles 
• data security best practices.
• A highly autonomous and proactive mindset. You are a quick learner who can self-motivate, prioritize needs, and deliver results in a dynamic environment.

And extra credit if you have experience in any of the following! 

• Experience with Snowpark.
• Experience with containerization and orchestration (Kubernetes is a nice to have).
• Familiarity with the Identity Access & Management (IAM) domain.
• Experience building developer-friendly, API-driven applications using REST and/or gRPC.

#LI_Hybrid

P24587_3348467

Auth0 is an easy-to-implement, authentication and authorization platform designed by developers for developers. We make applications’ login boxes safe, secure, and seamless for anyone logging in.

The Auth0 Data Engineering Team

Within Auth0, the Data Engineering team builds solutions to support analytics needs for the whole organization and is in charge of the Data Platform. It is divided into 3 groups:

• Pipeline team, sitting closer to the Platform team and data producers and in charge of the efficient data ingestion and provision of quick access to unmodeled data
• Warehouse team sitting closer to the business teams and data consumers and in charge of modeling the data in the data warehouse to abstract away the complexity for data consumers, simplifying the organization’s analysis, reporting and decision-making
• Interface team responsible for creating and managing connections between the data platform and various external systems (internal or external facing), making sure everyone has access to consistent and reliable data

The Senior Data Engineer Opportunity

Reporting to the manager of the Data Engineering Pipeline team, the senior data engineer will be a key player in ensuring the reliability and efficiency of our core data platform. This role is crucial, providing the stable data foundation that not only 'runs the business' day-to-day but also directly empowers the organization to unlock growth and build innovative new products. We are looking for an autonomous and proactive engineer who can take ownership of our data ingestion pipelines, work closely with platform teams and data producers, and onboard new data from various internal and external systems. You will be part of a team creating robust, scalable data solutions using a modern, best-in-class toolset.

What you’ll be doing 

• Own and operate our critical data pipelines and infrastructure, participating in the team's support rotation to ensure high availability and business continuity.
• Lead troubleshooting efforts to fix complex pipeline or infrastructure issues, demonstrating a willingness to go beyond the direct scope of the team to find resolutions.
• Manage the data onboarding lifecycle, working with stakeholders to integrate new internal and external data sources into our platform using our suite of tools.
• Develop and deploy robust, scalable data solutions using modern tools and technologies like Snowflake, dbt, Airflow, and Terraform.
• Continuously learn and advocate for modern technologies and best practices to improve data delivery and engineering efficiency.

What you’ll bring to the role

• 5+ years of software development experience, with at least 3+ years working on large-scale data systems.
• Strong proficiency in SQL for data manipulation and Python for data pipeline development.
• Hands-on experience building and operating data pipelines in a cloud environment (AWS preferred).
• Hands-on experience with the modern data stack, specifically:
• Data Warehousing: Snowflake
• Data Transformation: dbt
• Infrastructure as Code: Terraform
• Experience with data ingestion, streaming, and event-driven architecture (e.g., Kafka, CDC, Snowpipe).
• Knowledge of data security and data privacy best practices
• A strong understanding of data modeling principles 
• data security best practices.
• A highly autonomous and proactive mindset. You are a quick learner who can self-motivate, prioritize needs, and deliver results in a dynamic environment.

And extra credit if you have experience in any of the following! 

• Experience with Snowpark.
• Experience with containerization and orchestration (Kubernetes is a nice to have).
• Familiarity with the Identity Access & Management (IAM) domain.
• Experience building developer-friendly, API-driven applications using REST and/or gRPC.

P24586_3348463

#LI_Hybrid

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

As a Cloud Engineer, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 6+ YEARS of experience, a growth mindset and a drive to make a lasting impact. 

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Role responsibilities

• Design GCP-native architectures using services such as BigQuery, Dataflow (Apache Beam), Cloud Composer (Airflow), Pub/Sub, Cloud Storage, Vertex AI, and Cloud Run
• Build and maintain data pipelines — batch and streaming — following medallion architecture patterns (Bronze / Silver / Gold)
• Implement infrastructure as code using Terraform and manage deployments via Cloud Build or equivalent CI/CD tooling
• Define and apply GCP landing zone standards including IAM, VPC, Shared VPC, Private Service Connect, and Org policies
• Develop end-to-end Lakehouse solutions on Databricks — including Delta Lake table design, Unity Catalog governance, and MLflow model tracking
• Write and optimise PySpark and SQL workloads for large-scale transformations and feature engineering
• Configure Databricks clusters, job scheduling, auto-scaling, and cost controls in a GCP (DBX on GCP) environment
• Implement Databricks Workflows and Asset Bundles for orchestration and deployment automation
• Advise clients on Databricks platform adoption, including migration pathways from legacy Hadoop or on-premise data warehouses
• Lead technical workshops and requirements-gathering sessions with client technical and business teams
• Produce high-quality client-facing deliverables: architecture diagrams, technical specifications, migration runbooks, and data dictionaries
• Present solution designs and progress updates to client stakeholders — adapting technical communication to audience level (CTO to Business Analyst)
• Manage technical dependencies, risks, and issues across delivery workstreams — escalating to Delivery Managers as appropriate
• Participate in sprint ceremonies and maintain delivery velocity within Agile/Scrum or Kanban frameworks
• Implement data quality frameworks using tools such as Great Expectations, dbt tests, or Databricks Delta constraints
• Support data catalogue initiatives and metadata management using Dataplex or Unity Catalog
• Ensure GDPR/data residency compliance is embedded into solution design from the outset
• Support practice leads in responding to RFPs and RFIs — contributing to effort estimation, solution sizing, and proposal narrative
• Contribute to internal knowledge-sharing — through documentation, runbooks, and team enablement sessions
• Stay current with GCP and Databricks product roadmaps and proactively identify opportunities to introduce new capabilities to clients

Must have qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience
• 6+ years of hands-on professional experience in cloud data engineering or GCP platform roles.
• Google Cloud Professional Data Engineer or Professional Cloud Architect certification
• Databricks Certified Associate Developer for Apache Spark or Databricks Certified Data Engineer certification
• BigQuery — advanced SQL, partitioning, clustering, cost optimization
• Cloud Storage, Cloud Functions, Cloud Run
• Dataflow (Apache Beam) — batch & streaming pipelines
• Cloud Composer / Airflow — DAG authoring and management
• Pub/Sub — event-driven architectures
• Vertex AI — model serving and Pipelines exposure
• IAM, VPC, Org Policies — security and governance
• Cloud Build / Artifact Registry — CI/CD and containerization
• Terraform — infrastructure as code on GCP
• Looker / Looker Studio — reporting layer familiarity
• PySpark — DataFrame API, optimization, broadcast joins
• Delta Lake — ACID transactions, time travel, Z-ordering
• Unity Catalog — governance, lineage, access control
• Databricks Workflows / Job orchestration
• Databricks on GCP — cluster config, instance pools
• MLflow — experiment tracking, model registry
• dbt on Databricks or BigQuery
• Databricks Asset Bundles / CI/CD integration
• Python — data engineering and scripting proficiency
• SQL — advanced analytical queries
• Git / version control — branching, PR workflows
• Docker — containerization basics
• Unit testing and data pipeline testing practices
• REST API integration patterns

Nice to have qualifications  

• Experience with Azure or AWS alongside GCP — hybrid cloud delivery experience
• Familiarity with commercetools, Contentful, or other composable commerce/content platforms
• Exposure to Salesforce Marketing Cloud data connectors or CDPs
• Knowledge of Generative AI / LLM integration patterns — Vertex AI GenAI Studio, Gemini APIs
• Experience with Databricks Agent Framework or LangChain for agentic AI workloads
• Apache Kafka or Confluent Cloud for event streaming architectures
• Google Cloud Professional Machine Learning Engineer
• HashiCorp Terraform Associate.
• Experience in luxury, retail, or FMCG verticals — understanding of product data models and PIM systems

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

The benefits  

This is a Full Time position based in Bengaluru

Beyond a competitive compensation package, we offer: 

• Flexibility, with remote and hybrid work options (country-dependent) 
• Career advancement, with international mobility and professional development programs 
• Learning and development, with access to cutting-edge tools, training and industry experts 

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

Your application process

Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud!

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

DevOps Lead: 

Top consumer brands like Nestle, Kimberly Clark, Natures Bounty, Johnson & Johnson, Mondelez, Kellogg to name a few rely on CommerceIQ suite of products to make efficient business decisions on a daily basis. It is critical to have services which run high quality data and algorithms that drive business decisions for our customers in a timely manner. As a DevOps you are responsible for building scalable, extensible, secure infrastructure on cloud for CommerceIQ’s applications and data science teams. 

In this role, you will work with a couple of Infra/DevOps SDEs and partner with engineering managers to achieve CommerceIQ’s QoQ goals. As a DevOps lead, you will play a crucial role in upkeep security, cost, deployment infrastructure and maintain/develop services owned by Infra/DevOps team.

A successful candidate will be obsessed with technology and relentlessly raise the bar on the architecture, design and quality of code delivered while aggressively pursuing optimizations to meet cost and scale SLAs. The candidate should be capable of managing a fast-paced delivery schedule and influence and drive a high-level engineering strategy with the leadership, as well as take a hands-on approach to implementing that strategy.

Functional level Expectations

• You should possess advanced knowledge of AWS and other software design approaches to guide the DevOps team in designing infrastructure that caters to scale, concurrency. Preferably AWS certified.
• You should be able to work in situations where you can use your prior expertise and judgment to determine goals, identify constraints, and propose an actionable plan. 
• Your work is typically focused on working with multiple teams’ architecture and product solutions. 
• You should be able to lead the design and implementation that are extensible and scalable
• For continuous integration and deployment
• For multi cloud deployments
• For DR of various services with CiQ infrastructure
• You should be able to influence as a “team lead”, management decisions and priorities and actively mentor to create force multipliers
• You should drive teams to adhere to engineering best practices in SDLC like code coverage, acceptance testing, CI/CD and design patterns that ensure consistency and standardization of architecture
• You should proactively simplify code, identify bottlenecks and resolve team architecture deficiencies. 
• You should be able to work along with other SDEs on their team, build relationships with stakeholders including customers, product managers, cross functional partners and external partners and integrate for a cohesive launch. 

Required Skills

• At least 6-10 years of technology experience including 3+ years of working experience in cloud 
• Ideal candidate should have handled operations, deployment and security of multiple SaaS/B2C products
• Deep knowledge of Python, Cloud or GoLang and one of the public clouds
• Good knowledge of log collection designs like EFK and metric collection tools like newrelic, Prometheus/Grafana or SignalFx
• Good knowledge in design, creation and consumption of RESTful API, Micro service architectures on public clouds preferably AWS
• Excellent analytical, communication and coding skills is a must.
• Thorough orientation towards code reviews, coding/design standards and documentation
• Good knowledge in designing with messaging systems such as SQS, Kafka.
• Good knowledge in designing with ETL pipelines using AWS Step, Azkaban, Airflow
• Good knowledge of any big data engine like Spark would be an advantage.

Below is a brief description of the charter for Infra team (subject o product/business deliverables)

Prometheus / Grafana 

K8s metrics and deployment metrics

We use newrelic(NR) for log collection and operational metrics. But certain shortcomings and solved problems in Prometheus/Grafana might force us to move away from NR. Apart from the prometheus track, the lead will have to work with all. stakeholders [apps/DS] to migrate from OCD to K8s, with all balance and checks in place

EFK stack

Log collection and analysis is via newrelic and it’ll cost us as we move more applications to K8s. We need to optimise or explore options like EFK stack of logs or sumo logic etc 

Security audit

We need to be proactive and do frequent security audits of our applications. We need a security center with all our documentation. Place to store the docs/questionnaires we filled for our clients etc. 

BCP 

We need to audit all our services for disaster recovery and develop a BCP across the company.

CI/CD 

The lead is expected to enforce git branching and set code cov, style check guidelines across teams and projects. E.g Publishing the guidelines for Java project, NodeJS project, Python project. Establishing average code cov metrics, running static code analysis, findbug and other security code scanning tools

Infra services

The Infra team also has many services, especially crucial services like BSS (CSS) . These infra services should set the benchmark for DevOps best practices in the org. 

Azkaban

Azkaban is our ETL orchestrator. It's run in-house and has custom code deployed. Maintenance of Azkaban to match growth is needed. Exploration and guidance to use other orchestrators like airflow, step function, astronomer is also expected

AWS admin and access / SF admin and access / AWS/SF cost , unit cost for client

Constant efforts to identify and reduce costs

AWS partnership [case studies, blogs, trainings, tech conf talks]

Cost savings across all our infrastructure.

SOC2 and other compliance 

Automate our soc2 process with diligence. This is more important as we expand to other pillars of soc2 and ISO.

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The role  

As a Data Architect, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 10+ YEARS of experience, a growth mindset and a drive to make a lasting impact. 

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Role responsibilities

Must have qualifications

To be considered for this role, you must meet the following essential qualifications:

• Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or equivalent professional experience
• 10+ years of progressive experience in data architecture, data platform engineering, or enterprise BI/analytics roles
• Demonstrable experience as a lead data architect on at least two large-scale enterprise data platform programmes
• 3NF — operational and transactional layer design
• Dimensional modelling — Kimball star/snowflake, slowly changing dimensions
• Data Vault 2.0 — hubs, links, satellites, business keys
• Data mesh & domain-oriented data product design
• Architecture Decision Records (ADRs) and C4 modelling
• Data contract design — schema, SLAs, versioning
• Data catalogue & metadata management design
• Data quality framework design and governance policy
• BigQuery — advanced design, partitioning, clustering, BI Engine
• Dataflow (Apache Beam) — streaming and batch architecture
• Cloud Composer / Airflow — orchestration design
• Pub/Sub — event-driven data product patterns
• Dataplex — data cataloguing, lineage, data quality
• Vertex AI Pipelines — ML feature pipeline integration
• Cloud Storage — data lake zone design (raw/curated/serving)
• Terraform — IaC standards and landing zone design
• Databricks Lakehouse — medallion architecture, zone design
• Delta Lake — ACID, time travel, schema evolution, Z-ordering
• Unity Catalog — governance, lineage, access control, data products
• Databricks Workflows and Asset Bundles — lifecycle automation
• PySpark — advanced optimization, broadcast, AQE, dynamic pruning
• dbt on Databricks — transformation layer standards
• Databricks on GCP — cluster policy, instance pools, cost governance
• MLflow — model registry integration with data product layer
• Unity Catalog — fine-grained access, row/column security
• Dataplex — data mesh governance on GCP
• Data lineage — column-level lineage design and tooling
• GDPR, data residency, and privacy-by-design principles
• Data stewardship operating models
• Metadata standards — Dublin Core, OpenLineage, OpenMetadata
• Google Cloud Professional Data Engineer or Professional Cloud Architect certification
• Databricks Certified Professional Data Engineer or Databricks Certified Associate Developer for Apache Spark
• TOGAF, Zachman, or equivalent enterprise architecture framework certification.

Nice to have qualifications  

• Azure Synapse / Microsoft Fabric — cross-cloud architecture experience
• Apache Iceberg or Apache Hudi — open table format evaluation and migration experience
• Event-driven architecture — Apache Kafka, Confluent Cloud, or Pub/Sub advanced patterns
• Generative AI integration patterns — RAG pipelines, vector stores (AlloyDB, Vertex AI Vector Search), LLM-as-data-product
• Exposure to composable commerce data models — product, pricing, inventory, order domains (commercetools, SFCC, SAP Commerce)
• Experience in luxury, retail, or FMCG verticals — multi-brand data architectures, PIM/DAM integration patterns
• OpenMetadata or Collibra — enterprise-grade data catalogue implementation
• Familiarity with Salesforce Marketing Cloud data connectors or Customer Data Platforms (CDPs)
• Google Cloud Professional Machine Learning Engineer
• CDMP (Certified Data Management Professional) — DAMA certification
• HashiCorp Terraform Associate

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

The benefits  

This is a Fulltime position based in Bengaluru. 

Beyond a competitive compensation package, we offer: 

• Flexibility, with remote and hybrid work options (country-dependent) 
• Career advancement, with international mobility and professional development programs 
• Learning and development, with access to cutting-edge tools, training and industry experts 

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

Your application process

Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential.

⚠️ Beware of recruitment fraud!

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

Job Overview 

We are looking for a bright and exceptional Engineering Lead to join our Technology team. In this role, you will work closely with Product Managers, Subject Matter Experts, Data Scientists and Software Engineers to design, build, and optimize scalable data pipelines for our Data Platform. The ideal candidate has strong hands-on experience in distributed data processing, expertise in architecting Data Pipelines and operational skills to drive efficiency and speed.

Key Responsibilities:

• Work closely with the product and other teams to understand business requirements and translate them into robust engineering solutions.
• Architect, build and maintain data solutions and pipelines to meet business requirements.
• Engage and lead a team of talented technologists and establishing engineering best practices.
• Act as a point of contact for managing and driving production defects & stability improvements to resolution
• Oversee end-to-end data workflows from ingestion, transformation, and storage to data lake in both batch and streaming environments.
• Drive improvements in performance, reliability, and scalability of data pipelines 

Required Skills & Qualifications:

• A bachelor’s degree in computer science, Math, or other technical fields with 6-8 years of experience, Fintech domain is a plus.
• Demonstrated contribution to end-to-end delivery of enterprise-grade software
• Experience on Data Engineering, Data Lakes, Data Warehousing, Data Pipelines, Data Analytics tools.
• Experience using open-source Big Data technologies such as Spark, Hadoop, Elasticsearch, Kafka.
• Hands-on experience in enterprise application development
• Strong SQL skills and experience working with relational and NoSQL databases.
• Experience in cloud technologies is a plus
• Demonstrates advanced proficiency in Python for building scalable data pipelines, automating workflows
• Experience building scalable ETL/ELT data pipelines and data lakes/warehouses.
• Familiarity with workflow orchestration tools (Airflow, ADF, Glue Workflow, etc.).
• Solid understanding of CI/CD, version control, and DevOps practices.
• Experience working in agile, collaborative environments.
• Attention to detail and quality, and the ability to work well in and across teams
• Ability to advocate & influence multiple stakeholders
• Excellent problem-solving, communication, and leadership skills.
• Experience in leading a team of highly skilled engineers

Arcesium's Personal Data Privacy Notice for Candidates is linked here. 

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview

Retail and Selection is the engine behind Coupang’s massive product catalog, ensuring we offer the right products at the right price with the best availability. As we scale, the complexity of managing millions of SKUs and thousands of vendor relationships grows exponentially.
We are looking for a Staff Data Analyst to join the Retail and Selection team. In this role, you will be the technical architect of our data strategy, transforming raw market signals and internal metrics into a competitive advantage. You will work on projects that define the quality, availability, and depth of data needed to optimize our selection, pricing, and inventory health. You will use your deep expertise in SQL, ETL development, and data integrity to ensure Coupang’s leadership has the insights needed to dominate the retail landscape.

What You Will Do

• Data Strategy & Governance: Lead high-impact projects to improve the quality and depth of selection data, ensuring "source of truth" reliability for multi-billion dollar business decisions.
• Pipeline & ETL Mastery: Architect and maintain robust data ETL processes to integrate disparate signals from market trends, vendor performance, and customer demand.
• AI & Prompt Engineering: Leverage Large Language Models (LLMs) and advanced prompt engineering to automate catalog categorization, extract insights from unstructured vendor data, and accelerate internal analytical workflows.
• Knowledge Management: Own and evolve the Retail Team Knowledge Base, ensuring that technical documentation, data dictionaries, and business logic are centralized, searchable, and up-to-date for Data Analysis using AI tools.
• Business Empowerment: Support the onboarding of business users, designing training programs and self-service dashboards that enable Category Managers and Vendors to make data-driven decisions independently.
• Advanced Decision Modeling: Structure large-scale datasets to build decision models for SKU rationalization, automated replenishment, and competitive benchmarking.
• Optimization & Simulation: Run complex simulations to predict the impact of selection changes on customer retention and long-term profitability.
• Stakeholder Influence: Translate complex analytical findings into clear, actionable narratives for executive stakeholders across Retail and Supply Chain teams.
• Mentorship: Act as a technical beacon for the analytics community, guiding senior and junior analysts in their technical development and problem-solving frameworks.

Basic Qualifications

• Experience: 5+ years of relevant working experience in a data analytics or business intelligence role.
• Technical Stack: Expert-level proficiency in SQL and Python/R for data extraction and manipulation.
• AI Proficiency: Practical experience with prompt engineering and using generative AI tools to solve data problems or automate content generation.
• Visualization: Mastery of data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to non-experts.
• Communication: Business-level fluency in English with a proven ability to teach and onboard non-technical business users.

Preferred Qualifications  

• Data Engineering: Hands-on experience with version control (GitHub) and workflow orchestration tools like Airflow.
• Content & Documentation: Experience managing internal wikis (e.g., Confluence, Notion) or building structured knowledge bases for large organizations.
• Domain Expertise: Previous experience in Retail, E-commerce selection management, or Demand Forecasting.
• Quantitative Depth: Strong knowledge of statistics and ML techniques (e.g., elasticity modeling, clustering for customer segmentation).

Type of work model 

• Hybrid 
  
  

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

Please complete the attached Internal Transfer Request Form and submit.   

Please make sure to apply with your Coupang e-mail address.   

Company Introduction  

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant and reliable force in South Korean commerce.   

We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.  

Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. 
  

Role Overview

Retail and Selection is the engine behind Coupang’s massive product catalog, ensuring we offer the right products at the right price with the best availability. As we scale, the complexity of managing millions of SKUs and thousands of vendor relationships grows exponentially.
We are looking for a Staff Data Analyst to join the Retail and Selection team. In this role, you will be the technical architect of our data strategy, transforming raw market signals and internal metrics into a competitive advantage. You will work on projects that define the quality, availability, and depth of data needed to optimize our selection, pricing, and inventory health. You will use your deep expertise in SQL, ETL development, and data integrity to ensure Coupang’s leadership has the insights needed to dominate the retail landscape.

What You Will Do

• Data Strategy & Governance: Lead high-impact projects to improve the quality and depth of selection data, ensuring "source of truth" reliability for multi-billion dollar business decisions.
• Pipeline & ETL Mastery: Architect and maintain robust data ETL processes to integrate disparate signals from market trends, vendor performance, and customer demand.
• AI & Prompt Engineering: Leverage Large Language Models (LLMs) and advanced prompt engineering to automate catalog categorization, extract insights from unstructured vendor data, and accelerate internal analytical workflows.
• Knowledge Management: Own and evolve the Retail Team Knowledge Base, ensuring that technical documentation, data dictionaries, and business logic are centralized, searchable, and up-to-date for Data Analysis using AI tools.
• Business Empowerment: Support the onboarding of business users, designing training programs and self-service dashboards that enable Category Managers and Vendors to make data-driven decisions independently.
• Advanced Decision Modeling: Structure large-scale datasets to build decision models for SKU rationalization, automated replenishment, and competitive benchmarking.
• Optimization & Simulation: Run complex simulations to predict the impact of selection changes on customer retention and long-term profitability.
• Stakeholder Influence: Translate complex analytical findings into clear, actionable narratives for executive stakeholders across Retail and Supply Chain teams.
• Mentorship: Act as a technical beacon for the analytics community, guiding senior and junior analysts in their technical development and problem-solving frameworks.

Basic Qualifications

• Experience: 5+ years of relevant working experience in a data analytics or business intelligence role.
• Technical Stack: Expert-level proficiency in SQL and Python/R for data extraction and manipulation.
• AI Proficiency: Practical experience with prompt engineering and using generative AI tools to solve data problems or automate content generation.
• Visualization: Mastery of data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to non-experts.
• Communication: Business-level fluency in English with a proven ability to teach and onboard non-technical business users.

Preferred Qualifications  

• Data Engineering: Hands-on experience with version control (GitHub) and workflow orchestration tools like Airflow.
• Content & Documentation: Experience managing internal wikis (e.g., Confluence, Notion) or building structured knowledge bases for large organizations.
• Domain Expertise: Previous experience in Retail, E-commerce selection management, or Demand Forecasting.
• Quantitative Depth: Strong knowledge of statistics and ML techniques (e.g., elasticity modeling, clustering for customer segmentation).

Type of work model 

• Hybrid 
  
  

Details to consider 

• Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 
   

Privacy Notice  

• Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ 

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

We are experts in data, working to make it cost-effective, understandable, and trustworthy. We build pipelines processing billions of events a day and are stewards of canonical data warehouses and datasets delivering products for Stripe Users while embedding with teams to build their data products.  We are experts in using the Stripe Data Platform and to scale we lead the data culture and data education to enable product teams to own their data. We invest in [AI] Data Ops to scale incident handling and serve as an escalation path for data incidents to minimize their impact. The Data Engineering Solutions team will work closely with product teams delivering trustworthy data / backend code / and innovative (AI) tools/platforms/services for data.

What you’ll do

We're looking for a person who could drive the Data Engineering Solutions Team in solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of Data Engineering tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities.

You will:

• Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success.
• Partner with our recruiting team to attract and hire top talent.
• Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency.
• Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders.
• Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data.
• Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
• Have an opportunity to work with Spark, Flink, Kafka, Trino, Pinot, Airflow, Scala, Java, SQL, and Python and many other big data technologies.
• Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion.
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team.

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

We’re looking for someone who has: 

• 10+ Years of engineering experience with 5+ Years of hands-on experience building+operating data systems/pipelines, datasets/data warehouses, infrastructure, and leading small teams to deliver exceptional solutions.
• A strong engineering background and passion for data.
• Prior experience with writing and debugging data pipelines using a distributed data framework (Spark / Hadoop / Trino / etc)
• An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
• Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
• Extreme customer focus, with a commitment to partnering with Product Managers, leaders, and other Stripe engineers to understand their use cases.
• Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs.
• Thrive with high autonomy and responsibility in an ambiguous environment.
• Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment.

Preferred qualifications

• Expertise in Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, AWS Cloud, and influencing open-source contributions is a plus.
• Experience creating and maintaining Data Marts / Data Warehouses to power business reporting needs
• Experience working with Product or Go-To-Market (GTM - Sales/Marketing) teams
• Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions.
• Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide.

Who We Are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the Team

The Batch Compute Infrastructure team at Stripe manages the foundational infrastructure, tooling, and distributed systems behind Stripe's massive-scale batch processing environments, currently encompassing over 5,000 computational nodes. Powered primarily by Hadoop, Spark, and Celeborn, these systems are the backbone for several core asynchronous financial, analytical, and regulatory workflows at Stripe, operating at petabyte scale.

What you’ll do -
You will support a team of engineers focused on building the tooling, infra and systems for operating Spark, Hadoop and Celeborn at Stripe. In addition to helping define the roadmap for these systems, you will be interacting with many other managers and their teams at Stripe, who rely on the Data processing Infra team to deliver efficient and scalable services to our customers. You will work with both the finance and engineering organization (infrastructure & product) to define, measure and monitor the cost efficiency of these systems. 

Responsibilities

• Drive Strategic Vision: Define the multi-year roadmap for Stripe’s Batch Compute Infrastructure, leading complex architectural shifts and modernization.
• Lead and Scale: Build, mentor, and aggressively scale a high-performing team of engineers, proactively investing in their career development and fostering a culture of operational excellence.
• Ensure Operational Rigor: Maintain unwavering reliability for a Tier-0 infrastructure processing tens of thousands of daily workloads, proactively mitigating risks and managing complex on-call telemetry.
• Cross-Functional Orchestration: Collaborate deeply with data platform teams, finance, and user groups to define compute efficiency metrics, execute massive-scale cost optimization strategies, and guarantee compliance with global financial regulations.
• Technical Stewardship: Provide technical guidance in architecture reviews, evaluating critical cost, performance, and reliability trade-offs in distributed systems design involving Hadoop, Spark, AWS cloud primitives, and modern metastores.

Who You Are

Minimum requirements

• 10+ years of professional software development and engineering experience.
• 3+ years of direct engineering management experience, successfully building and operating high-velocity technical teams.
• Deep technical background in building, scaling, and maintaining large-scale distributed data systems or Tier-0 infrastructure using open-source tools (e.g., Hadoop, Spark, Celeborn, Airflow, Kafka).
• Proven track record of driving significant infrastructure efficiency, managing capacity planning, and making data-driven cost-performance trade-offs.
• Experience working effectively in highly cross-functional, global organizations.

Preferred requirements

• Experience managing remote or geographically distributed engineering teams.
• Familiarity with managing a massive fleet of Linux servers, on-premise Hadoop clusters, and modern cloud data architectures (e.g., AWS S3, Graviton).
• Demonstrated ability to navigate strategic ambiguity and deliver complex, multi-quarter infrastructural projects from inception to completion.
• Deep empathy for internal data users with a passion for building robust developer tooling and abstractions.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world’s largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the team

Role Overview

We are seeking an analytically-driven Data Analyst to join our Finance & Strategy team at Stripe. This role bridges the gap between data science and financial planning, requiring someone who can transform complex business data into actionable financial insights. You will build sophisticated dashboards, develop predictive models, and serve as the technical backbone for our FP&A and GTM analytics initiatives. This is a unique opportunity for a data professional with financial acumen to directly influence strategic business decisions in a high-growth fintech environment.

What You'll Do

Financial Data Analytics & Modeling

• Design, build, and maintain financial dashboards for FP&A, Revenue Operations, and GTM teams using Tableau, Power BI, or Looker
• Develop automated financial reporting solutions that reduce manual effort and improve data accuracy
• Create sophisticated data models to support budgeting, forecasting, variance analysis, and scenario planning
• Build predictive models for revenue forecasting, customer lifetime value, churn analysis, and unit economics

Business Intelligence & Reporting

• Partner with Finance Business Partners and FP&A teams to translate business requirements into technical solutions
• Design and implement data infrastructure for financial planning cycles (monthly/quarterly reviews, annual budgets, long-range planning)
• Develop self-service analytics capabilities enabling finance teams to access real-time business insights
• Create executive dashboards tracking key financial and operational metrics (ARR, bookings, retention, CAC, LTV)

Data Engineering & Analytics Infrastructure

• Write complex SQL queries to extract, transform, and analyze large datasets from multiple source systems
• Build ETL pipelines to integrate financial data from ERP, CRM, billing, and data warehouse systems
• Ensure data quality, consistency, and governance across financial reporting systems
• Optimize database performance and data architecture for scalability

Strategic Analysis & Insights

• Conduct deep-dive analyses on business performance, identifying trends, anomalies, and opportunities
• Support strategic initiatives through ad-hoc financial modeling and what-if scenario analysis
• Translate complex data findings into clear, actionable recommendations for leadership
• Collaborate with Data Science teams to develop advanced analytics and ML models for finance use cases

Required Qualifications

Technical Skills

• Must Have: Advanced SQL proficiency (complex joins, window functions, CTEs, query optimization)
• Must Have: Expert-level experience with at least one BI tool (Tableau, Power BI, Looker, or Qlik)
• Must Have: Advanced Excel/Google Sheets skills (pivot tables, complex formulas, data modeling)
• Preferred: Python or R for data analysis, automation, and statistical modeling
• Preferred: Experience with cloud data platforms (Snowflake, BigQuery, Redshift, Databricks)
• Preferred: Knowledge of ETL tools (dbt, Airflow, Fivetran) and version control (Git)

Financial & Business Acumen

• Experience in data analytics within finance, FP&A, or revenue operations functions
• Strong understanding of financial statements (P&L, balance sheet, cash flow)
• Knowledge of key financial metrics: ARR, MRR, bookings, revenue recognition, CAC, LTV, gross margin, EBITDA
• Experience with financial planning processes: budgeting, forecasting, variance analysis, scenario modeling
• Understanding of SaaS/subscription business models and revenue recognition principles (ASC 606 preferred)

Analytical & Problem-Solving

• Proven ability to work with large, complex datasets and derive meaningful insights
• Experience building financial models and dashboards that drive executive decision-making
• Strong statistical analysis skills and understanding of data visualization best practices
• Track record of translating ambiguous business problems into structured analytical frameworks

Preferred Experience

• Background in fintech, payments, B2B SaaS, or high-growth technology companies
• Experience supporting GTM analytics (sales forecasting, pipeline analysis, quota setting)
• Familiarity with finance systems: NetSuite, Anaplan, Adaptive Planning, Salesforce, Stripe Billing
• Exposure to data science methodologies and machine learning concepts
• Previous work in cross-functional environments collaborating with finance, data science, and business teams

Key Competencies

• Business Acumen: Ability to understand complex business models and translate them into data requirements
• Technical Excellence: Deep technical skills with commitment to code quality and best practices
• Communication: Exceptional ability to explain technical concepts to non-technical stakeholders
• Stakeholder Management: Experience partnering with senior leaders and influencing through data
• Ownership Mindset: Self-directed with ability to manage multiple priorities and drive projects to completion
• Continuous Learning: Curiosity to learn new tools, techniques, and business domains
• Attention to Detail: Commitment to data accuracy and quality in high-stakes financial reporting

Education

• Bachelor's degree in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, or related quantitative field
• Advanced degree (MBA, MS in Analytics/Data Science) or relevant certifications (CFA, CPA, data analytics certifications) a plus

What Makes This Role Unique This position sits at the intersection of data engineering, business intelligence, and strategic finance. You'll have the autonomy to architect solutions that shape how Stripe makes multi-million dollar decisions, while working with cutting-edge data technologies and some of the brightest minds in fintech. If you're energized by the prospect of building the analytics infrastructure that powers a global payments platform, this role is for you.

We’re hiring someone who does both — and does both at speed.

This role sits inside the Central AI Initiatives team within the Marketing Team. You will own the full loop: identify a high-impact business problem, conceive the AI-powered solution, build the production system, ship it, and own the outcome — as a single person. The problems change every few weeks as the company’s priorities shift. One month you’re building a multi-agent system for merchant risk detection. The next, you’re deploying an ops copilot that processes 20,000+ events a day. What stays constant is the expectation that you close the loop end-to-end — from a messy business brief to a live system with metrics moving — in days, not quarters. This is not a research role. It is not a PM role. It is not a data science role. It is a builder role that requires all three — simultaneously.

You Know Who You Are You have deep expertise across the full building journey:

1. Decompose business problems from first principles. When a messy brief lands, you break it into data, models, integrations, automations, and human touchpoints — and make the right call on what to build vs. buy vs. defer.
2. Design and build the full system yourself. Architecture, backend services, data pipelines, LLM orchestration, frontend — you own the spec nobody writes for you. You write production code, not demos that die after a meeting.
3. Ship to production and own the outcome. Phased rollouts, alert thresholds, business metrics. When something breaks, you fix it. When numbers are below target, you know Why.
4. Switch altitude — technical depth to C-suite context. Debug a model’s internals in the morning. Present the roadmap to leadership in the afternoon. Review legal terms for an AI partnership before end of day.
5. Multiply AI capability across the organisation. You make teams across Sales, Marketing, Risk, and Engineering better at identifying and executing AI opportunities on their own — through frameworks, reference tools, and workshops that change Behaviour.

You’ve been using AI tools for over a year — Claude Code or Cursor is your default environment, not a novelty. You orchestrate agents, build with skills and MCPs. AI assistance is muscle memory. You’re a polyglot — picking up new stacks fast because AI handles the ramp. You thrive in ambiguity and default to action.

You will be a good fit if you bring

– Founder mindset: you’ve started something (a company, a product, a team) and taken it from zero to live with your own hands. You don’t wait for specs.
– 3–5 years building software with at least 1–2 years building AI/ML-powered products in production. Depth matters more than years — the right 2-year person beats the wrong 8-year person every time.
– Full-stack capability: backend services, data pipelines (Kafka, Airflow), LLM orchestration (OpenAI, Anthropic, Gemini), frontends (React), and deployment infrastructure (GCP, Docker). You don’t wait for other teams to unblock you.
– LLM & agent depth: hands-on with multi-agent systems, RAG, prompt engineering, and production AI pipelines — not just API wrappers.
– Product instinct: you ask “why” before “how.” You can scope a business problem down to a shippable prototype and articulate business value to non-technical stakeholders.
– Speed & autonomy: you can take a problem from discovery to demo in under two weeks. You move faster than the process and create structure only where it helps.
– Influence without authority: you align stakeholders across Sales, Risk, Engineering, and Legal by being clear, credible, and fast — without having direct reports in any of those functions.

You will not be a good fit if you

You need detailed specs handed to you. You prefer deep specialisation over breadth. You’re uncomfortable with ambiguity. You optimise for code elegance over customer outcomes. You hand off after designing or after shipping. You treat “not my job” as a valid answer. You need a stable roadmap to do your best work. You still thrive living in a 2-week sprint.

What the work has looked like

Projects change frequently. Recent examples from this team:

– Browser-based AI Agent — autonomous web navigation agent that crawls merchant websites, detects payment gateways at checkout, and places test orders. Used by Risk Ops for mystery shopping and fraud detection. Headless browser + LLM-driven navigation + real-time Slack alerting.
– Ops Copilot Platform — full-stack employee activity intelligence: Rust-based macOS agents for screen OCR and audio transcription (Whisper), centralised server (Bun + Hono + PostgreSQL), React dashboard with WebSocket streaming, VLM-powered workflow extraction.
– Pre-Churn Alerting — Airflow DAGs processing risk events and merchant data to generate daily intelligence alerts delivered to Slack for proactive retention.
– Analytics Platform Rollout — end-to-end evaluation, procurement, legal approval, and org-wide rollout of PostHog as the product analytics platform. 

How to apply

We screen on one thing before anything else: evidence that you have built something technically demanding end-to-end and taken it live.
– Send a note (300–500 words) on the most technically complex system you’ve built — the problem it solved, the architecture choices, what broke in production and how you fixed it, and what you’d do differently now.
– Optionally: a link to something running in production, a GitHub repo with real commits, or a case study.

If the note shows the instincts we’re looking for, we’ll reach out within a week. The process is short: one technical problem set, two focused conversations, a final discussion with the team Lead. 

Why Razorpay

1. Scale that matters — billions of transactions, thousands of merchants. What you build goes live on India’s largest payments platform. You know within weeks whether it Worked.
2. Impact at scale — help transform India’s leading payments platform into the country’s first AI-native payments company. The problems are core: merchant growth, payment routing, revenue expansion — not peripheral. 3. Small team, real autonomy — no bureaucracy between your idea and production. Direct access to the CEO and VP Engineering. If the idea is good, it ships.

About Us

Razorpay was founded by Shashank Kumar and Harshil Mathur in 2014. Razorpay is building a new-age digital banking hub (Neobank) for businesses in India. Our mission is to enable frictionless banking and payments experiences for businesses of all shapes and sizes. We started as a B2B payments company, and today, we process billions of dollars of payments for lakhs of businesses across India. We are the leading payments provider in the country and have been the first to bring to market most major innovations in the past 7 years. Razorpay currently processes multi-billion dollar payments on an annualised basis, touching 200Mn+ end customers through top clients like Airtel, Goibibo, Yatra, Ola, Swiggy, Zomato, Cred etc. We have raised around USD $740M+ in funding from marquee investors like GIC, Alkeon Capital, Lone Pine Capital, TCV, Sequoia Capital, Tiger Global, Ribbit Capital, Matrix Partners and many stellar angels.

Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

At ZoomInfo we encourage creativity, value innovation, demand teamwork, expect accountability and cherish results. If you are collaborative, take initiative, and get stuff done we want to talk to you! We have high aspirations for the company and are looking for the right people to help fulfil the dream. We strive to continually improve every aspect of the company and use cutting-edge technologies and processes to delight our customers and rapidly increase revenue. 

Role Overview: ZoomInfo is seeking a Data Analyst III to join the Data Operations and Analysis team. This role partners closely with Product, Engineering, and Research teams to enhance data infrastructure, improve data quality, and deliver actionable insights that drive business impact.

Key Responsibilities:

• Develop a deep understanding of data systems, pipelines, and infrastructure.
• Analyze current data processes, identify gaps, and recommend scalable improvements.
• Drive initiatives to enhance data accuracy, coverage, and efficiency.
• Collaborate cross-functionally with Data Engineering, Product, and Research teams.
• Perform advanced data analysis and present insights in a clear, structured manner.
• Mentor junior analysts and contribute to team capability building.
• Work independently to explore data, propose solutions, and execute projects end-to-end.

Core Competencies:

• Strong analytical thinking and problem-solving ability.
• Ability to work in ambiguous environments and drive clarity.
• Effective communication with both technical and non-technical stakeholders.
• High attention to detail and strong organizational skills.
• Self-driven with the ability to manage multiple priorities.

Required Qualifications:

• 5+ years of experience in analytics, data operations, or quantitative research.
• Advanced proficiency in SQL, Python, BigQuery, and Excel.
• Strong understanding of ETL processes and data quality challenges.
• Experience working with large-scale datasets.
• Familiarity with AI/ML concepts including NLP and data modeling.

Preferred Qualifications:

• Experience building or deploying AI/ML solutions.
• Exposure to tools like Tableau or Looker Studio.
• Experience with Databricks, AWS, or Airflow.
• Background in product-driven or project-based environments.

Impact: This role plays a critical part in shaping the future of ZoomInfo’s data ecosystem by improving data reliability, scalability, and strategic value.

#LI-SG2

#LI-Hybrid

At Rockstar Games, we create world-class entertainment experiences.   

Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly motivated environment where you can learn and collaborate with some of the most talented people in the industry.    

Rockstar is seeking a Senior Data Engineer to join our online services team, building an innovative game analytics platform and tools to better understand our players and enhance their experience across our titles.   

This is a full-time, in-office position based in Rockstar’s large game development studio in Bangalore, India.

WHAT WE DO

• The Rockstar Games Data Engineering team provides insights and actionable results to a wide variety of teams across the organization in support of their decision making.  
• We work with petabyte-scale data in Azure and Databricks, building both real-time and batch pipelines that power analytics, machine learning, and player experience improvements.  

RESPONSIBILITIES

• Design, build, and own real-time and batch data pipelines in Azure Databricks using Spark, Airflow, and modern orchestration and build tools.   
• Drive engineering excellence by implementing robust testing practices (unit, integration), code review standards, and CI/CD automation.
• Implement automated data quality frameworks and validation of pipelines.
• Build observability systems to monitor data integrity, drift, and system health. Troubleshoot complex data infrastructure and pipeline issues.
• Design analytics-ready datasets that power business intelligence and operational reporting.
• Partner with diverse stakeholders (including Data Scientists, Analysts, and ML Engineers) to define use cases and build robust data products.
• Translate large datasets into actionable insights for leadership and product teams.
• Explore emerging technologies including modern data platforms, distributed computing frameworks, build proof-of-concept solutions, and continuously improve platform scalability, performance, and cost efficiency 

REQUIREMENTS

• 6+ years’ experience in building data pipelines, distributed systems, or large scale data platforms on major clouds (Azure preferred).  
• Strong software engineering fundamentals: design patterns, testing strategies (unit, integration) code review practices, system design thinking Experience with big data frameworks such as Spark or Databricks.
• 4+ years’ experience using Python for maintainable, testable data engineering and Spark or Databricks for large scale processing.  
• Experience with workflow orchestration tools such as Airflow. 
• Experience with streaming technologies, notably Kafka, in distributed environments.  
• Proven work handling high volume structured and unstructured data (logs, telemetry, text) at scale.  
• Familiarity with AWS, Azure, or GCP data services and building cloud native data architectures.  
• Cross functional collaborator with strong communication skills for explaining complex systems to technical and non technical audiences.

PLUSES

Please note that these are desirable skills and are not required to apply for the position.

• Databricks platform experience (Delta Lake, Unity Catalog, Workflows).  
• Containerization and orchestration (Docker, Kubernetes). 
• Experience with Snowflake, Cassandra, or other modern data platforms.
• Experience building, maintaining, or scaling ML infrastructure.
• Experience with CI/CD and deployment tools (TeamCity, Octopus) and Artifact Repositories (JFrog, Proget).
• Experience with Terraform.
• Gaming industry experience or passion for games.  

HOW TO APPLY

Please apply with a CV and cover letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.

Rockstar is committed to creating a work environment that promotes equal opportunity, dignity and respect. In line with this commitment, Rockstar will provide reasonable accommodations to qualified job applicants with disabilities during the recruitment process in order for such applicants to be considered for the position for which they are applying, as well as to qualified employees to enable them to perform the essential functions of their roles. If you need more information about Rockstar’s reasonable accommodation policies or process, or need to request an accommodation, please notify your recruiter during the interview process.  

If you’ve got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, race, or any other protected category.

#LI-RN1

Overview of Role

We are seeking a highly skilled Cloud Data Engineer to join our Managed Services team. In this role, you will be the technical backbone for our enterprise clients, responsible for designing, building, and maintaining high-performance data platforms using Snowflake and Azure Databricks. You will act as a trusted advisor, ensuring that our customers' data ecosystems are scalable, secure, and cost-optimized across multi-cloud environments.

Key Responsibilities

• Platform Engineering: Design and implement end-to-end data lakehouse architectures using Azure Databricks (Delta Lake),Azure HDInsights and Snowflake Cloud Data Warehouse.
• Pipeline Development: Build scalable, metadata-driven ETL/ELT pipelines using Azure Data Factory (ADF), PySpark, and SnowSQL, including ingestion workflows from HDInsight-managed Hadoop and Kafka clusters.
• Managed Services Support: Provide Tier-3 technical support for client environments, including performance tuning, complex bug fixes, and architectural optimizations.
• Multi-Cloud Integration: Oversee data movement and integration strategies across Azure, AWS, and GCP to ensure seamless "Data Everywhere" capabilities for clients.
• Cost & Performance Governance: Monitor and optimize Snowflake credit consumption and Databricks cluster usage to ensure clients receive maximum ROI.
• Security & Compliance: Implement enterprise-grade security including Role-Based Access Control (RBAC), Row-Level Security (RLS), and data masking (Dynamic Data Masking in Snowflake / Unity Catalog in Databricks).

Required Technical Skillset

Experience & Qualifications

• Experience: 5+ years in Data Engineering, with at least 3 years of hands-on experience in both Snowflake and Databricks.
• Managed Services Background: Proven experience supporting external customers with strict SLAs and complex governance requirements.
• Multi-Cloud (Plus): Direct experience deploying Snowflake or Databricks on AWS or GCP is highly desirable.
• Certifications (Preferred): * SnowPro Core or Advanced Architect
• Databricks Certified Data Engineer Professional
• Microsoft Certified: Azure Data Engineer Associate (DP-203)

Job Description – Data Engineer

About the Role

We are looking for a  candidate who is  passionate about building scalable data pipelines, optimizing data workflows, and ensuring high data quality across systems. Candidates should demonstrate strong technical foundations, the ability to work independently, and a willingness to collaborate in a dynamic environment.

Core Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines to support business and analytical needs.
• Work extensively with Databricks, Python, and PySpark to process large datasets.
• Build and manage DAGs using Apache Airflow for workflow orchestration.
• Collaborate with cross-functional teams to understand data requirements and translate them into efficient engineering solutions.
• Develop and optimize complex SQL queries and participate in data modeling activities for relational and cloud data warehouses.
• Work with Amazon S3 for data storage, ingestion, partitioning, and integration within broader data lake and pipeline ecosystems.
• Ensure high standards of data quality, reliability, and performance across all data processes.
• Contribute to documentation, best practices, and continuous improvement initiatives.

Core Technical Requirements

1. Python Programming

• Strong experience writing clean, efficient Python code for data manipulation, automation, scripting, and ETL workflows.
• Familiarity with widely used data libraries (e.g., pandas, numpy).

1. Databricks

• Hands-on experience with Databricks for distributed data processing.
• Proficiency in PySpark, Delta Lake, notebooks, and building scalable pipelines.

1. Orchestration Tools

• Apache Airflow (Required): Ability to design, implement, and maintain complex DAGs for scheduling and orchestrating workflows.
• Argo Workflows (Preferred): Experience with Kubernetes-native orchestration platforms is an added advantage.

1. SQL Skills

• Advanced SQL expertise including writing complex queries, query optimization, and working with relational/cloud data warehouses.
• Experience in data modeling and performance tuning.

1. Cloud Storage (Amazon S3)

• Practical knowledge of S3 for ingestion, storage, data partitioning, access control, and integration as part of data lake architectures.

Experience Level

 2–5 years in Data Engineering or related roles..

Preferred Personal Attributes

• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, evolving environment.

Designation  :DevOps Engineer
Location: Bangalore
Work Mode: Hybrid
Experience Required: 2–4 years

Job Summary

We are looking for a Professional Services OPS Engineer to support client-facing data
operations and workflow execution. This role focuses on job monitoring, issue resolution,
data sharing, and operational support across multiple platforms to ensure reliable and
timely client deliverables.

Key Responsibilities

• Monitor and troubleshoot job failures in Visual Cron, Argo, and Databricks
• Perform root-cause analysis and implement fixes to maintain workflow stability
• Build, schedule, and maintain workflows using Visual Cron, Argo, Databricks Jobs, and
Snowflake Tasks
• Manage data sharing and deliveries via Databricks Share, Snowflake Share, S3, and SFTP
• Push MDE and non-MDE data to client environments post job success
• Support monthly refresh cycles, reruns, backfills, and ad-hoc operational requests
• Handle client and internal PS inquiries related to deliverables and missing files
• Collaborate with internal teams to improve operational processes

Required Skills

• Hands-on experience with job schedulers (Visual Cron preferred)
• Argo or Airflow workflow orchestration
• Strong working knowledge of Databricks
• SQL for data validation and troubleshooting
• Python for scripting and automation
• Basic knowledge of S3
• Experience with SFTP-based data deliveries

Good to Have

• Snowflake Tasks and Snowflake Share
• Azure Blob Storage Exposure and Experience supporting client-facing or production systems.

Want to build the next generation of AI-powered analytics and intelligent agents for observability and security use cases? Passionate about leveraging cutting-edge machine learning, large language models, and GPU-accelerated inference to transform how organizations understand and act on their logs data? Come talk with us!

As a Senior Machine Learning Engineer, you’ll build the intelligence behind the next generation of agentic AI systems that reason over massive, heterogeneous log data. You’ll combine machine learning, prompt engineering, context engineering and rigorous evaluation to create autonomous AI agents that help organizations understand and act on their data in real time.

You’ll be part of a small, high-impact team shaping how AI agents understand complex machine data. This is an opportunity to work on cutting-edge LLM infrastructure and contribute to defining best practices in context engineering and AI observability.

Location: Noida/ Bengaluru (Hybrid)

Responsibilities

• Design, implement, and optimize agentic AI components, including tools, memory management, and prompts.
• Develop and maintain golden datasets by defining sourcing strategies, working with data vendors, and ensuring quality and representativeness at scale.
• Prototype and evaluate novel prompting strategies and reasoning chains for model reliability and interpretability.
• Collaborate cross-functionally with product, data, and infrastructure teams to deliver end-to-end AI-powered insights.
• Operate autonomously in a fast-paced, ambiguous environment - defining scope, setting milestones, and driving outcomes.
• Ensure reliability, performance, and observability of deployed agents through rigorous testing and continuous improvement.
• Maintain a strong bias for action—delivering incremental, well-tested improvements that directly enhance customer experience.

Required Qualifications

• B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or a related field.
• 6+ years of hands-on industry experience with demonstrable ownership and delivery.
• Strong understanding of machine learning fundamentals, data pipelines, and model evaluation.
• Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus.
• Working knowledge of LLM core concepts, prompt design, and agentic design patterns.
• Experience with distributed systems and dealing with large amounts of data.
• Strong communication skills and a passion for shaping emerging AI paradigms.

Desired Qualifications

• Experience leading a team of engineers.
• Prior experience building and deploying AI agents or LLM applications in production.
• Familiarity with modern agentic AI frameworks (e.g., LangGraph, LangChain, CrewAI).
• Experience with ML infrastructure and tooling (PyTorch, MLflow, Airflow, Docker, AWS).
• Exposure to LLM Ops - infrastructure optimization, observability, latency, and cost monitoring.

About Us

Sumo Logic, Inc. empowers the people who power modern, digital business. Sumo Logic enables customers to deliver reliable and secure cloud-native applications through its Sumo Logic SaaS Analytics Log Platform, which helps practitioners and developers ensure application reliability, secure and protect against modern security threats, and gain insights into their cloud infrastructures. Customers worldwide rely on Sumo Logic to get powerful real-time analytics and insights across observability and security solutions for their cloud-native applications. For more information, visit www.sumologic.com.

Sumo Logic Privacy Policy. Employees will be responsible for complying with applicable federal privacy laws and regulations, as well as organizational policies related to data protection.

DevOps Lead: 

Top consumer brands like Nestle, Kimberly Clark, Natures Bounty, Johnson & Johnson, Mondelez, Kellogg to name a few rely on CommerceIQ suite of products to make efficient business decisions on a daily basis. It is critical to have services which run high quality data and algorithms that drive business decisions for our customers in a timely manner. As a DevOps you are responsible for building scalable, extensible, secure infrastructure on cloud for CommerceIQ’s applications and data science teams. 

In this role, you will work with a couple of Infra/DevOps SDEs and partner with engineering managers to achieve CommerceIQ’s QoQ goals. As a DevOps lead, you will play a crucial role in upkeep security, cost, deployment infrastructure and maintain/develop services owned by Infra/DevOps team.

A successful candidate will be obsessed with technology and relentlessly raise the bar on the architecture, design and quality of code delivered while aggressively pursuing optimizations to meet cost and scale SLAs. The candidate should be capable of managing a fast-paced delivery schedule and influence and drive a high-level engineering strategy with the leadership, as well as take a hands-on approach to implementing that strategy.

Functional level Expectations

• You should possess advanced knowledge of AWS and other software design approaches to guide the DevOps team in designing infrastructure that caters to scale, concurrency. Preferably AWS certified.
• You should be able to work in situations where you can use your prior expertise and judgment to determine goals, identify constraints, and propose an actionable plan. 
• Your work is typically focused on working with multiple teams’ architecture and product solutions. 
• You should be able to lead the design and implementation that are extensible and scalable
• For continuous integration and deployment
• For multi cloud deployments
• For DR of various services with CiQ infrastructure
• You should be able to influence as a “team lead”, management decisions and priorities and actively mentor to create force multipliers
• You should drive teams to adhere to engineering best practices in SDLC like code coverage, acceptance testing, CI/CD and design patterns that ensure consistency and standardization of architecture
• You should proactively simplify code, identify bottlenecks and resolve team architecture deficiencies. 
• You should be able to work along with other SDEs on their team, build relationships with stakeholders including customers, product managers, cross functional partners and external partners and integrate for a cohesive launch. 

Required Skills

• At least 6-8 years of technology experience including 3+ years of working experience in cloud 
• Ideal candidate should have handled operations, deployment and security of multiple SaaS/B2C products
• Deep knowledge of Python, Cloud or GoLang and one of the public clouds
• Good knowledge of log collection designs like EFK and metric collection tools like newrelic, Prometheus/Grafana or SignalFx
• Good knowledge in design, creation and consumption of RESTful API, Micro service architectures on public clouds preferably AWS
• Excellent analytical, communication and coding skills is a must.
• Thorough orientation towards code reviews, coding/design standards and documentation
• Good knowledge in designing with messaging systems such as SQS, Kafka.
• Good knowledge in designing with ETL pipelines using AWS Step, Azkaban, Airflow
• Good knowledge of any big data engine like Spark would be an advantage.

About the Role

At Degreed, we help organizations build and measure the skills that power their future. As our data volume and platform complexity continue to grow, we are investing in scalable, high-performance data architecture to support long-term product innovation and business expansion. This role exists to move us beyond maintenance and into the next phase of data platform evolution. As a Senior Data Engineer, you will design and optimize the core data layer that enables internal teams and clients to access reliable, performant, and trusted data at scale.

We are seeking candidates with 5  to 10 years of relevant experience in data engineering, demonstrating strong ownership of data platform components and the ability to operate in complex, high-scale environments.

Key Skills

• Advanced proficiency in Snowflake and SQL, demonstrated by designing performant queries, optimizing warehouse usage, and improving cost efficiency across large-scale datasets
• Strong experience with dbt and dimensional data modeling, including building modular, scalable models and enforcing testing and documentation standards
• Proven experience building and orchestrating data pipelines using tools such as Airflow, Meltano, or similar orchestration frameworks in production environments
• Experience working with infrastructure-as-code and containerized environments, such as Kubernetes and Terraform, supporting reliable and reproducible data platform deployments
• Demonstrated ability to design data architectures that scale with increasing data volume and concurrency, reducing bottlenecks and improving system reliability
• Experience leading or contributing to complex data engineering projects, managing tasks through tools such as Jira and Confluence, and delivering against defined milestones
• Proven experience mentoring data engineers, conducting code reviews, and elevating team standards through shared best practices
• Experience operating in environments with production support responsibilities, including on-call rotations and incident resolution processes
• Ability to collaborate cross-functionally with analytics, product, engineering, and business stakeholders to translate data requirements into robust technical solutions
• Ability to leverage AI tools and technologies relevant to data engineering workflows, such as AI-assisted query optimization, pipeline monitoring, documentation generation, or anomaly detection
  
  

Key Responsibilities

• Design and build a scalable, high-performance data layer used across internal teams and external client-facing use cases
• Optimize and refactor existing data models in Snowflake to improve efficiency, maintainability, and performance
• Develop and maintain reliable, production-grade data pipelines that ensure accuracy, timeliness, and consistency of business-critical data
• Implement infrastructure and orchestration improvements that strengthen platform stability, scalability, and observability
• Collaborate with analytics and product teams to define data requirements and translate them into scalable data solutions
• Conduct code reviews and mentor team members to elevate engineering standards and promote best practices
• Participate in on-call rotations and incident response processes to maintain 24/7 data platform reliability
• Contribute to architectural decisions and long-term roadmap planning to ensure the data platform supports future business growth
  
  

P-1348

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is important to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

As a Senior Software Engineer working on the Data Platform team you will help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, Applied AI and many more. You will develop a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, data consumption layers etc. You will do this using the latest, bleeding-edge Databricks product and other tools in the data ecosystem - the team also functions as a large, production, in-house customer that dog foods Databricks and guides the future direction of the product.

The impact you will have:

• Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance.
• Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protections and ease of shareability for the Data Intelligence Platform as we transition to a public company.
• Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.
• Design the base ETL framework used by all pipelines developed at the company.
• Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product.
• Build reliable data pipelines and solve data problems using Databricks, our partner’s products and other OSS tools. Provide early feedback on the design and operations of these products.
• Establish conventions and create new APIs for telemetry, debug, feature and audit event log data, and evolve them as the product and underlying services change.
• Represent Databricks at academic and industrial conferences & events.

What we look for:

• 6+ years of industry experience 
• 4+ years of experience providing technical leadership on large projects similar to the ones described above - ETL frameworks, metrics stores, infrastructure management, data security.
• Experience building, shipping and operating reliable multi-geo data pipelines at scale.
• Experience working with and operating workflow or orchestration frameworks, including open source tools like Airflow and DBT or commercial enterprise tools.
• Experience with large-scale messaging systems like Kafka or RabbitMQ or commercial systems.
• Excellent cross-functional and communication skills, consensus builder.
• Passion for data infrastructure and for enabling others by making their data easier to access.

This is a hybrid role. At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline.

Key Responsibilities:

• Engineering & AI: Be part of a team of backend engineers working in an agile environment, using mainly Python, while identifying opportunities to integrate AI and LLM tools to automate repetitive data mapping and vendor integration tasks.
• Collaborate: Partner with stakeholders to analyze requirements, design scalable solutions, and ensure successful implementation of core data services.
• Testing: Ensure quality releases by developing corresponding Unit Tests and Test Automations, leveraging AI-assisted testing tools where applicable to increase coverage.
• Architecture: Architect and design robust, scalable, and secure solutions for complex business needs and external data ingestion.
• Optimization: Identify performance bottlenecks and provide innovative solutions, including using AI for proactive system monitoring and anomaly detection.
• Culture: Foster a culture of learning by sharing new techniques, AI technologies, and engineering best practices.

What We Look For:

• Python Expertise: 5+ years of hands-on experience in software development using server-side and core Python technologies is a must.
• AI & Innovation: Proven experience or strong interest in integrating AI/LLM capabilities into backend workflows to improve data processing or engineering efficiency.
• Async Development: Expertise with Django Rest Framework and async development using Celery.
• Databases: Proficiency in databases such as Postgres, MySQL, etc.
• Tech Stack: Strong experience with Restful APIs, Docker, AWS, Airflow, Sentry, and OpenSearch.
• Methodology: Proficiency in Test Driven Development (TDD), Continuous Delivery, and agile development methodologies.
• Version Control: Expertise in Git and Github.
• Problem Solving: Strong problem-solving skills and ability to design solutions for complex business requirements.
• Communication: Excellent communication and collaboration skills

Title: DevOps Engineer

Reporting to: Senior Director, Product Development
Location: Bengaluru (Bangalore)

Opportunity:

Responsibilities:

Infrastructure Development & Integration

• Design, implement, and manage cloud-native infrastructure (AWS, Azure, GCP) to support healthcare platforms, AI agents, and clinical applications.
• Build and maintain scalable CI/CD pipelines to enable rapid and reliable delivery of software, data pipelines, and AI/ML models.
• Design and manage Kubernetes (K8s) clusters for container orchestration, workload scaling, and high availability with integrated monitoring to ensure cluster health and performance
• Implement Kubernetes-native tools (Helm, Kustomize, ArgoCD) for deployment automation and environment management ensuring observability through monitoring dashboards and alerts
• Collaborate with Staff Engineers/Architects to align infrastructure with enterprise goals for scalability, reliability, and performance leveraging monitoring insights to inform architectural decisions.

System Optimization & Reliability

• Implement and maintain comprehensive monitoring, logging, and alerting mechanisms (Prometheus, Grafana, ELK, Datadog, AWS cloudwatch, AWS cloud trail) to ensure real-time visibility into system performance, resource utilization, and potential incidents.
• Implement monitoring, logging, and alerting mechanisms (Prometheus, Grafana, ELK, Datadog) to ensure system reliability and proactive incident response.
• Ensure data pipeline workflows (ETL/ELT, real-time streaming, batch processing) are observable, reliable, and auditable.
• Support observability and monitoring of GenAI pipelines, embeddings, vector databases, and agentic AI workflows.
• Proactively analyze monitoring data to identify bottlenecks, predict failures, and drive continuous improvement in system reliability.

Compliance & Security

• Support audit trails and compliance reporting through automated DevSecOps practices.
• Implement security controls for LLM-based applications, AI agents, and healthcare data pipelines, including prompt injection prevention, API rate limiting, and data governance.

Collaboration & Agile Practices

• Partner closely with software engineers, data engineers, AI/ML engineers, and product managers to deliver integrated, secure, and scalable solutions.
• Contribute to agile development processes including sprint planning, stand-ups, and retrospectives.
• Mentor junior engineers and share best practices in cloud-native infrastructure, CI/CD, Kubernetes, and automation.

Innovation & Technical Expertise

• Stay informed about emerging DevOps practices, cloud-native architectures, MLOps/LLMOps, and data engineering tools.
• Prototype and evaluate new frameworks and tools to enhance infrastructure for data pipelines, GenAI, and Agentic AI applications.
• Advocate for best practices in infrastructure design, focusing on modularity, maintainability, and scalability.

Requirements

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical discipline.
• 6+ years of experience in DevOps, Site Reliability Engineering, or related roles, with at least 3+ years building cloud-native infrastructure.
• Proven track record of managing production-grade Kubernetes clusters and cloud infrastructure in regulated environments.
• Experience supporting GenAI/LLM applications (e.g., OpenAI, Hugging Face, LangChain) and vector databases (e.g., Pinecone, Weaviate, FAISS).
• Hands-on experience supporting data pipeline products using ETL/ELT frameworks (Apache Airflow, dbt, Prefect) and streaming systems (Kafka, Spark, Flink).
• Experience deploying AI agents and orchestrating agent workflows in production environments.

Technical Proficiency

• Expertise in Kubernetes (K8s) for orchestration, scaling, and managing containerized applications.
• Strong proficiency in containerization (Docker) and Kubernetes ecosystem tools (Helm, ArgoCD, Istio/Linkerd for service mesh).
• Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, or Pulumi).
• Proficiency with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, ArgoCD, Spinnaker).
• Familiarity with monitoring and observability tools (Prometheus, Grafana, ELK, Datadog, AWS cloud watch and AWS cloud trail), including setting up dashboards, alerts, and custom metrics for cloud-native and AI systems.
• Good to have: knowledge of healthcare data standards (FHIR, HL7) and secure deployment practices for AI/ML and data pipelines.

Professional Skills

• Strong problem-solving skills with a focus on reliability, scalability, and security.
• Excellent collaboration and communication skills across cross-functional teams.
• Proactive, detail-oriented, and committed to technical excellence in a fast-paced healthcare environment.

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

• SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
• Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
• TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

About the Job

We are building a Customer Data Platform (CDP) designed to unlock the full potential of customer experience (CX) across our products and services. This role offers the opportunity to design and scale a platform that unifies customer data from multiple sources, ensures data quality and governance, and provides a single source of truth for analytics, personalization, and engagement.

As a key member of the data engineering team, you will architect and implement the pipelines, storage layers, and integrations that power our CDP. You’ll work with product, data science, and engineering stakeholders to deliver a robust platform that supports real-time decision-making, personalization at scale, and actionable customer insights.

This is a high-impact, hands-on engineering role where you’ll shape the data foundation that directly influences how we understand and serve our customers.

What You Will Be Doing

• Design and implement Five9’s Customer Data Platform solutions and enable production use cases for customers

• Design and develop highly scalable and resilient services for ingesting large-scale datasets

• Demonstrate strong ownership by ensuring operational excellence with a sharp focus on monitoring, observability, and system reliability

• Develop and orchestrate ETL/ELT pipelines using Apache Airflow

• Collaborate with cross-functional partners and lead technical initiatives independently end-to-end

• Design, build, and optimize distributed query engines such as Apache Spark or Snowflake to support complex data workloads

• Write, review, or provide feedback on technical design proposals from others

Skills

• 5–7 years of software/data engineering and data platform experience

• Extensive experience with data transformation and modeling, including advanced features and best practices

• Deep knowledge of Snowflake for data warehousing, including optimization, security, and cost management

• Good understanding of data streaming technologies such as Kafka/Kafka Connect

• Strong knowledge of highly scalable distributed systems, microservices, REST APIs

• Strong proficiency in object-oriented and/or functional programming languages such as Java, .NET, Python, and SQL for data processing, transformation, and pipeline development

• Knowledge of Apache Airflow for workflow orchestration is nice to have

• Understanding of containerization and Kubernetes concepts

• Experience with the AWS cloud platform and infrastructure-as-code practices

• Maintain high standards of code quality with a keen eye for test automation and operational excellence

• Track record of delivering scalable data engineering solutions that support analytics, machine learning, and operational use cases

• Excellent written and verbal communication and interpersonal skills

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent training, fellowship, or work experience

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience. 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries. 

We are proud of: 

• The work we do and the innovation we drive 
• Our values of share, care and dare 
• A workplace culture that fosters creativity, diversity and autonomy 
• Our borderless, global framework, which enables seamless collaboration 

The Role  

As a Data Engineer, you are passionate about experience innovation and eager to push the boundaries of what’s possible. You bring 4+ years of experience, a growth mindset and a drive to make a lasting impact. 

You will thrive in this role if you are: 

• A curious problem solver who challenges the status quo 
• A collaborator who values teamwork and knowledge-sharing 
• Excited by the intersection of technology, creativity and data 
• Experienced in Agile methodologies and consulting (a plus) 

Role & Responsibilities

• Design and build data pipelines: Develop scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) workflows for batch and streaming data processing.
• Manage data infrastructure: Maintain and optimize data storage solutions, such as data lakes (Cloud Storage) and data warehouses (BigQuery), to ensure scalability, performance, and reliability.
• Ensure data quality: Implement processes to guarantee the accuracy, integrity, and security of data throughout its lifecycle.
• Collaborate with teams: Work closely with data scientists, analysts, and software engineers to understand their data needs and deliver robust data solutions.
• Support machine learning: Operationalize machine learning models by building and maintaining the data pipelines that feed and integrate with Google's Vertex AI platform.
• Automate processes: Implement automation for manual data tasks and workflows to improve efficiency.
• Troubleshoot issues: Monitor and debug data systems and pipelines to ensure uninterrupted data delivery. 

Must have

To be considered for this role, you must meet the following essential qualifications: 

• Education: A Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field is typically required.
• Minimum 3 + Years of experience as a Data Engineer.
• Programming expertise: Proficiency in Python, SQL, and other languages like Java or Scala is common.
• GCP technologies: Hands-on experience with core GCP services is essential. Key services include:
• Data Processing: Dataflow, Dataproc, and Pub/Sub.
• Storage and Warehousing: BigQuery, Cloud Storage, and Cloud SQL.
• Orchestration: Cloud Composer (powered by Apache Airflow).
• Data fundamentals: Deep understanding of data modeling, data warehousing, and distributed systems.
• Big Data technologies: Experience with open-source tools like Apache Spark or Apache Beam.
• Testing and DevOps: Familiarity with CI/CD pipelines (e.g., Cloud Build), Git, and automated testing.
• Analytical skills: Strong problem-solving and analytical thinking abilities.
• Communication: Excellent communication skills to explain complex technical concepts to both technical and non-technical stakeholders.
• Certification (preferred): A Google Cloud Professional Data Engineer certification can boost a candidate's profile 

If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn. 

Commitment to reaching all kinds of people 

We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all. 

 The Benefits  

This is a Full-Time position based in Bengaluru, Gurugram, Ahmedabad and Pune.

Beyond a competitive compensation package, we offer: 

• Flexibility, with hybrid work options (country-dependent) 
• Learning and development, with access to cutting-edge tools, training and industry experts.

Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process. 

Your application process

Once you apply, our Talent Acquisition team will review your application. If your skills and experience align with the role, we’ll reach out for next steps. 

⚠️ Beware of recruitment fraud: Only engage with official Valtech email addresses ending in @valtech.com. 

We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know. 

About Valtech

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world. 

At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more. 

At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate. 

Are you ready to create what’s next? Join us.

Title: Principal Data Software Engineer

Location: Bengaluru (Bangalore)

Opportunity:

Get Well is seeking a visionary and technically adept Principal Data Software Engineer to design, develop and optimize our cloud-native data platform supporting AI, analytics, and clinical applications. This role is pivotal in architecting scalable, secure, and high-performance data processing systems within a regulated healthcare environment. 

The ideal candidate brings deep technical expertise in data engineering, data governance, cloud infrastructure and hands-on experience with healthcare data standards, EMR integration, and clinical ontologie. The candidate should have a proven record of building secure, scalable data platforms. This position reports to the Senior Director, Product Development. This role requires close collaboration with data engineers, product teams, AI engineers and compliance specialists to deliver accurate, accessible, and actionable data solutions.

Responsibilities:

Platform Architecture & Design

• Design and implement scalable, secure, and efficient data architectures (e.g., data lakehouse, medallion architecture) to support enterprise AI and analytics initiatives.
• Define technical specifications for data ingestion, transformation, storage, and access layers.
• Evaluate and recommend tools, frameworks, and cloud infrastructure to optimize performance, scalability, and cost-efficiency.
• Ensure architectural alignment with organizational AI, analytics, and clinical application goals.

Data Engineering & Operations

• Develop and maintain high-performance data pipelines for both batch and streaming data processing, leveraging tools such as Apache Spark, Databricks or Snowflake.
• Implement deployment and orchestration frameworks (e.g., Airflow, dbt, Spark, Databricks, Snowflake)
• Adhere to engineering best practices for CI/CD, observability, incident response, and SLA adherence
• Optimize data processing systems for performance, reliability, and reusability.

• Mentor engineers to foster technical growth and ensure alignment with best practices in data engineering.

Governance, Quality & Compliance

• Collaborate with data governance and compliance teams to implement data security, encryption, and access control policies in line with HIPAA, GDPR, and other regulations.
• Ensure data quality through validation, lineage tracking, and metadata management practices.
• Support the development and maintenance of data catalogs for discoverability and stewardship

Collaboration & Technical Leadership

• Partner with data engineers, product teams, and clinical informatics specialists to deliver integrated data solutions.
• Provide technical guidance and mentorship to junior engineers, fostering a culture of technical excellence and collaboration.
• Communicate complex technical designs and solutions to both technical and non-technical stakeholders effectively.
• Contribute to agile development practices, participating in code reviews, design discussions, and continuous improvement initiatives.

Innovation & Technical Expertise

• Stay informed about emerging trends in data engineering, cloud-native architectures, and healthcare data standards.
• Prototype and evaluate modern data frameworks and tools (e.g., Delta Lake, Apache Iceberg) to enhance platform capabilities.
• Communicate complex technical concepts to both technical and non-technical stakeholders.
• Advocate for best practices in data platform design to ensure scalability, explainability, and compliance in AI-driven systems.

Requirements:

Education & Experience

• Bachelor’s or Master’s degree in Computer Science or related technical discipline
• 12+ years of experience with at least 4+ years in data engineering or platform roles
• Proven track record of designing and implementing cloud-native data processing systems.

Technical Proficiency

• Advanced proficiency in Python, Scala, SQL, and distributed data processing frameworks such as Apache Spark.
• Hands-on experience with cloud-based data platforms (e.g., Databricks, Snowflake, BigQuery, or Redshift).
• Demonstrated ability to transform raw clinical data into curated, ML-ready datasets for analytics and AI applications.
• Hands-on expertise in healthcare data standards including FHIR, HL7, USCDI, and CCDA

Professional Skills

• Strong problem-solving skills with a focus on delivering scalable and maintainable solutions.
• Excellent collaboration and communication skills, with the ability to work effectively in cross-functional teams.
• Proactive, detail-oriented, and committed to driving technical excellence in a fast-paced environment.

About Get Well:

Now part of the SAI Group family, Get Well is redefining digital patient engagement by putting patients in control of their personalized healthcare journeys, both inside and outside the hospital. Get Well is combining high-tech AI navigation with high-touch care experiences driving patient activation, loyalty, and outcomes while reducing the cost of care. For almost 25 years, Get Well has served more than 10 million patients per year across over 1,000 hospitals and clinical partner sites, working to use longitudinal data analytics to better serve patients and clinicians. AI innovator SAI Group led by Chairman Romesh Wadhwani is the lead growth investor in Get Well. Get Well’s award-winning solutions were recognized again in 2024 by KLAS Research and AVIA Marketplace. Learn more at Get Well and follow-us on LinkedIn and Twitter.

Get Well is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.

About SAI Group:

• SAIGroup commits to $1 Billion capital, an advanced AI platform that currently processes 300M+ patients, and 4000+ global employee base to solve enterprise AI and high priority healthcare problems. SAIGroup - Growing companies with advanced AI; https://www.cnbc.com/2023/12/08/75-year-old-tech-mogul-betting-1-billion-of-his-fortune-on-ai-future.html
• Bio of our Chairman Dr. Romesh Wadhwani: Team - SAIGroup (Informal at Romesh Wadhwani - Wikipedia)
• TIME Magazine recently recognized Chairman Romesh Wadhwani as one of the Top 100 AI leaders in the world - Romesh and Sunil Wadhwani: The 100 Most Influential People in AI 2023 | TIME

P-1348

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Our engineering teams build technical products that fulfill real, important needs in the world. We always push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is important to making customers successful on our platform.

We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.

As a Staff Software Engineer working on the Data Platform team you will help build the Data Intelligence Platform for Databricks that will allow us to automate decision-making across the entire company. You will achieve this in collaboration with Databricks Product Teams, Data Science, Applied AI and many more. You will develop a variety of tools spanning logging, orchestration, data transformation, metric store, governance platforms, data consumption layers etc. You will do this using the latest, bleeding-edge Databricks product and other tools in the data ecosystem - the team also functions as a large, production, in-house customer that dog foods Databricks and guides the future direction of the product.

The impact you will have:

• Design and run the Databricks metrics store that enables all business units and engineering teams to bring their detailed metrics into a common platform for sharing and aggregation, with high quality, introspection ability and query performance.
• Design and run the cross-company Data Intelligence Platform, which contains every business and product metric used to run Databricks. You’ll play a key role in developing the right balance of data protections and ease of shareability for the Data Intelligence Platform as we transition to a public company.
• Develop tooling and infrastructure to efficiently manage and run Databricks on Databricks at scale, across multiple clouds, geographies and deployment types. This includes CI/CD processes, test frameworks for pipelines and data quality, and infrastructure-as-code tooling.
• Design the base ETL framework used by all pipelines developed at the company.
• Partner with our engineering teams to provide leadership in developing the long-term vision and requirements for the Databricks product.
• Build reliable data pipelines and solve data problems using Databricks, our partner’s products and other OSS tools. Provide early feedback on the design and operations of these products.
• Establish conventions and create new APIs for telemetry, debug, feature and audit event log data, and evolve them as the product and underlying services change.
• Represent Databricks at academic and industrial conferences & events.

What we look for:

• 12+ years of industry experience 
• 4+ years of experience building large scale distributed systems
• 5+ providing technical leadership on large projects similar to the ones described above - ETL frameworks, metrics stores, infrastructure management, data security.
• Experience building, shipping and operating reliable multi-geo data pipelines at scale.
• Experience working with and operating workflow or orchestration frameworks, including open source tools like Airflow and DBT or commercial enterprise tools.
• Experience with large-scale messaging systems like Kafka or RabbitMQ or commercial systems.
• Excellent cross-functional and communication skills, consensus builder.
• Passion for data infrastructure and for enabling others by making their data easier to access.

We are seeking an experienced and highly skilled Senior Data Scientist to lead our efforts in optimizing ad display on native Android surfaces. In this role, you will design and implement data-driven strategies to maximize ad effectiveness, user engagement, and revenue. You will collaborate closely with product managers, engineers, and cross-functional teams to drive innovation, improve ad relevance, and ensure a seamless user experience.

As a Senior Data Scientist, you’ll get to:

• Develop and refine data-driven ad optimization strategies tailored to native Android environments, focusing on user engagement, personalization, and revenue uplift.
• Design, implement, and improve predictive models for ad targeting, recommendation, and bidding strategies using cutting-edge machine learning and statistical techniques.
• Lead the design and analysis of experiments to test ad placements, formats, and targeting methods. Use data from A/B tests and multivariate testing to validate hypotheses and inform decisions.
• Analyze user behavior patterns to understand engagement and dropout points, leveraging insights to optimize ad positioning, timing, and relevance.
• Partner with product managers, engineers, designers, and marketing teams to align ad strategies with business objectives and user experience goals. Communicate insights and recommendations effectively to both technical and non-technical stakeholders.
• Ensure the scalability of ad models across a wide range of Android devices and varying network conditions. Work closely with engineering teams to deploy and monitor models in a production environment.
• Provide mentorship and guidance to junior data scientists, fostering a collaborative and innovative team environment. Lead by example in developing high-quality, scalable solutions for complex ad optimization challenges.

You’ll be a good fit if you have:

• PhD (preferred) or Master's Degree (required) in Computer Science, Data Science, Statistics, Machine Learning, or a related field.
• 6+ years of experience in data science or machine learning, with a strong focus on ad technology or user experience optimization.
• Demonstrable experience in working with ad serving, ad tech stacks, and optimization techniques, especially within Android or mobile ecosystems.
• Expertise in machine learning frameworks (TensorFlow, PyTorch, or similar).
• Advanced proficiency in Python, or Kotlin.
• Experience with data processing and pipeline tools (e.g., Spark, Hadoop, Airflow).
• Deep understanding of A/B testing, causal inference, and other experimentation methods.
• Familiarity with ad tech, programmatic advertising, and user behavior metrics, particularly in the context of mobile and Android platforms.
• Excellent analytical, problem-solving, and communication skills. Proven ability to articulate complex data science concepts to stakeholders across different domains.

 Nice to have: 

• Previous experience optimizing ad displays on native mobile or Android surfaces.
• Familiarity with the Android SDK and understanding of native Android UI/UX design principles.
• Knowledge of reinforcement learning, multi-armed bandit models, and contextual targeting techniques.

This role is based at our Bengaluru, India office and follows a Hybrid schedule that will be aligned with our Return to Office guidelines.

Build and operate the production backbone that takes models from Applied Sciences (AS) and delivers reliable, low-latency ML services across Tekion’s DMS, CRM, Digital Retail, Service, Payments, and enterprise products. You’ll own pipelines, microservices, CI/CD, observability, and runtime reliability—working hand-in-hand with Applied Sciences and Product to turn ideas into measurable dealer and consumer impact. 

Why this Role Matters 

• Accelerate the rollout of LLM-powered and agent-driven features across Tekion products. 

• Enable agentic workflows that automate, reason, and interact on behalf of users and internal stakeholders. 

• Operationalize secure, compliant, and explainable LLM and agentic services at scale. 

• Convert Applied Sciences models into scalable, compliant, cost‑efficient production services. 

• Standardize how models are trained, validated, deployed, and monitored across Tekion products. 

• Power real-time, context-aware experiences by integrating batch/stream features, graph context, and online inference. 

What You’ll Do 

• Turn Applied Sciences prototype models (tabular, NLP/LLM, recommendation, forecasting) into fast, reliable services with well-defined API contracts. 

• Integrate with the LLM Gateway/MCP, prompt/config versioning. 

• Build and orchestrate CI/CD pipelines. 

• Review data science models; refactor and optimize code; containerize; deploy; version; and monitor for quality. 

• Collaborate with data scientists, data engineers, product managers, and architects to design enterprise systems. 

• Monitor, detect, and mitigate risks unique to LLMs and agentic systems. 

• Implement prompt management: versioning, A/B testing, guardrails, and dynamic orchestration based on feedback and metrics. 

• Design batch/stream pipelines (Airflow/Kubeflow, Spark/Flink, Kafka) and online features linked to our domain graph. 

• Build inference microservices (REST/gRPC) with schema versioning, structured outputs, and stringent p95 latency targets. 

• Manage the model/feature lifecycle: feature store strategy, model/agent registry, versioning, and lineage. 

• Instrument deep observability: traces/logs/metrics, data/feature drift, model performance, safety signals, and cost tracking. 

• Ensure real-time reliability: autoscaling, caching, circuit breakers, retries/fallbacks, and graceful degradation. 

• Develop templates/SDKs/CLIs, sandbox datasets, and documentation that make shipping ML the default path. 

Desired Skills and Experience 

• 6+ years in ML engineering/MLOps or backend/platform engineering with production ML. 

• Experience with LLMs, retrieval systems, vector stores, and graph/knowledge stores. 

• Strong software engineering fundamentals: Python plus one of Java/Go/Scala; API design; concurrency; testing. 

• Hands-on with orchestration frameworks and libraries (LangChain, LlamaIndex, OpenAI Function Calling, AgentKit, etc.). 

• Knowledge of agent architectures (reactive, planning, retrieval-augmented agents), and safe execution patterns. 

• Pipelines and data: Airflow/Kubeflow or similar; Spark/Flink; Kafka/Kinesis; strong data quality practices. 

• Microservices and runtime: Docker/Kubernetes, service meshes, REST/gRPC; performance and reliability engineering. 

• Model ops: experiment tracking, registries (e.g., MLflow), feature stores, A/B and shadow testing, drift detection. 

• Observability: OpenTelemetry/Prometheus/Grafana; debugging latency, tail behavior, and memory/CPU hotspots. 

• Cloud: AWS preferred (IAM, ECS/EKS, S3, RDS/DynamoDB, Step Functions/Lambda), with cost optimization experience. 

• Security/compliance: secrets management, RBAC/ABAC, PII handling, auditability. 

Preferred Mindset 

• Product-oriented: You measure success by dealer and consumer outcomes, not just technical metrics. 
• Reliability- and safety-first: You move fast with guardrails, rollbacks, and clear SLOs. 
• Systems thinker: You design for multi-tenant scale, portability, and cost efficiency
• Collaborative: You translate between Applied Sciences, Product, and the Data & AI Platform; you document and teach. 

Senior Software Engineer  -  Senior Machine Learning Platform

Why This Role Matters 

This role powers Tekion’s AI‑native, end‑to‑end automotive platform by turning unified dealership data across DMS, CRM, Digital Retail, Service, and Payments into real‑time intelligence. You’ll operationalize a graph‑based contextual ecosystem so agents can retrieve the right context, enforce policy, and personalize experiences that drive measurable dealer outcomes. You’ll also build the resilient control layer - MCP and the LLM Gateway - that enables safe, cost‑efficient, multi‑provider LLM usage. Finally, you’ll define the standards for building, evaluating, deploying, and governing agentic systems so product teams can ship AI features quickly, safely, and at scale. In addition to enabling agentic systems powered by LLMs, this role also drives building the platform for classical ML models driving optimization across dealership operations.  

What Makes This Opportunity Unique 

This role offers direct, measurable impact on dealer outcomes and consumer experiences across Tekion’s Automotive Retail Cloud and Automotive Enterprise Cloud, with end‑to‑end ownership of an LLM control plane and gateway that serve multi‑tenant workloads under SLAs and, quality and cost guardrails. You’ll leverage a rich vertical dataset and domain graph spanning sales, service, parts, F&I, accounting, and consumer touchpoints to power context‑aware agents and retrieval‑augmented generation. You’ll also shape core levers - agent orchestration patterns, evaluation frameworks, and safety guardrails - so improvements in latency, reliability, evaluation quality, and safety translate into dealer KPIs like upsell, cycle time, CSAT, and service revenue.  You’ll also maintain and enhance the platform to support classical supervised and unsupervised ML models . 

Responsibilities 

• Build and run the LLM control plane/gateway: smart routing, rate limits/quotas, failover, and token/cost tracking. 

• Ship a unified API and SDKs (REST/gRPC) with normalized schemas, structured outputs, caching, and full observability (traces/logs/metrics). 

• Enforce safety and privacy by default: content filtering, prompt/response validation, and PII redaction. 

• Enable multi‑model, multi‑vendor use LLMs with automated canarying and versioning. 

• Own the agent runtime: tool registry, permissions, function calling, grounding, and retrieval. 

• Design orchestration patterns (sequential, planner‑executor, streaming) and manage agent state and long‑running workflows. 

• Enabling platform components for training and scoring pipelines for classical ML (e.g., XGBoost/LightGBM/linear/trees) and deep models; standardize experiment tracking and packaging. 

• Create components to Monitor model and data drift, retraining and tuning models as needed to maintain accuracy and relevance. 

• Add human‑in‑the‑loop review and safe‑actioning before agents touch dealer systems. 

• Evolve the domain graph and entity resolution; build reliable data ingestion pipelines. 

• Serve real‑time context to agents (profiles, inventory, pricing, appointments, service history) with access controls and lineage. 

• Power retrieval with hybrid search (graph + vector + keyword) and smart cache/TTL to balance accuracy, latency, and cost. 

• Run continuous offline/online evaluations for quality, factuality, bias, and safety for the platform sanity. 

• Define SLOs for latency (p50/p95), uptime, and cost view capabilities; enable autoscaling and spend controls. 

• Maintain a model/agent registry, versioning, approvals, audit trails, and reproducibility; support compliances where needed. 

• Provide templates/CLIs, sandboxes, and docs so product teams can build and ship fast; mentor engineers and champion MLOps and AI safety best practices. 

Desired Skills & Experience 

• 5 - 7 years building large‑scale data/ML or platform systems; strong software engineering fundamentals (Abstracted API design, concurrency, distributed systems). 

• Production experience with Python plus one of Java/Scala/Go; microservices and API design. 

• MLOps at scale: pipelines (Airflow/Kubeflow), tracking/registry (MLflow), CI/CD for models, A/B testing, shadow/canary, and online feature computation (Spark/Flink/Kafka). 

• Cloud and containers: AWS (preferred), plus Docker/Kubernetes; performance, reliability, and cost engineering in multi‑tenant SaaS. 

• Practical ML knowledge (feature engineering, training, evaluation, drift detection); experience deploying models that power user‑facing workflows. 

• Built or operated an LLM gateway/control plane: provider adapters, routing/policies, caching, quota/rate‑limit, cost and token accounting. 

• Agentic systems: tool use/function calling, orchestration frameworks, human‑in‑the‑loop, safety/guardrails, and online evaluation/telemetry. 

• Graph and retrieval: knowledge graphs (e.g., Neo4j/Neptune/TigerGraph), GraphQL, vector search (e.g., pgvector/Qdrant/Milvus), hybrid retrieval patterns. 

Preferred Mindset 

• Platform‑as‑product: obsess over developer experience, paved roads, and clear SLAs. 

• Thinks in systems - observability, fallback, access control are core, not afterthoughts. 

• Passionate about AI - enjoys enabling real-world LLM and agentic use cases. 

• Cost‑aware builder: you treat latency and dollars as first‑class metrics and design for graceful degradation. 

• Vendor‑agnostic thinker: choose the right model/provider per use case; build for portability and resilience. 

• Documentation and teaching: you make complex systems understandable; you uplevel teams. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Staff Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Data Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

We are looking for a Staff Data Engineer to drive the execution and scaling of project44’s data platform.This role sits at the intersection of Data Engineering, Data Science, and Product, with a mandate to translate architectural vision into reliable, scalable systems used across teams.

You will partner closely with other data engineers to implement platform direction, establish engineering standards, and ensure consistent, high-quality execution across data systems. Your focus will be on solving complex data challenges, driving adoption of best practices, and enabling teams to build efficiently on a shared foundation.

As AI reshapes how data systems operate, you will also help integrate agentic and GenAI-powered workflows into data pipelines and developer workflows—improving automation, observability, and system intelligence.

What You’ll Do

Drive Platform Execution

• Translate architectural direction into production-grade systems across ingestion, transformation, and serving layers.

Establish Standards & Best Practices

• Define and enforce patterns for data modeling, pipeline design, observability, testing, and data quality across teams.

Solve Complex Data Problems

• Own and resolve high-impact technical challenges related to scale, latency, reliability, and cost efficiency.

Enable Consistency Across Teams

• Work across multiple teams to drive adoption of shared data models, tooling, and engineering practices.

Build Scalable Data Systems

• Develop and optimize pipelines and data systems for performance, maintainability, and long-term scalability.

Integrate AI-Native Workflows

• Implement agentic and GenAI-driven workflows to automate data operations, improve monitoring, and accelerate development.

Mentor & Raise the Bar

• Act as a technical leader within the team, mentoring junior engineers and elevating engineering quality across the organization.

What We’re Looking For

8–10+ years in Data Engineering or Software Engineering, with a strong track record of building and scaling production-grade systems.

Technical Expertise

• Strong programming skills (Python preferred, Java/Scala a plus) and deep experience with modern data technologies (Spark, Snowflake, Databricks).

Data Systems & Execution

• Proven ability to build and operate reliable, scalable data pipelines and systems in production environments.

Data Modeling & Warehousing

• Strong experience in data modeling, warehousing, and building analytics- and ML-ready datasets.

Distributed Systems & Trade-offs

• Ability to navigate trade-offs across performance, cost, reliability, and scalability in cloud-native systems.

AI & Modern Tooling

• Experience leveraging GenAI or agentic tools to improve developer productivity, automate workflows, or enhance data systems.

Cross-Team Influence

• Experience working across teams to drive alignment, adoption of standards, and consistent execution.

Communication & Leadership

• Strong communication skills and the ability to influence technical decisions across teams.

Preferred Skills

• Experience with real-time and event-driven systems (Kafka, streaming architectures)
• Familiarity with orchestration tools (Airflow, Argo) and containerization (Docker, Kubernetes)
• Experience with data governance and access control (RBAC)
• Exposure to analytics and BI tools (Looker, Tableau)
• Experience building shared data platforms or internal tooling
• Background in logistics, supply chain, or high-scale operational systems

What Success Looks Like (6–12 Months)

• Successfully implemented core data platform patterns across multiple teams
• Improved data reliability, observability, and quality in critical pipelines
• Reduced inconsistency in data models and engineering practices across teams
• Enabled faster development and deployment of data and ML workflows
• Introduced AI-driven improvements in data workflows and developer productivity
• Acted as a key technical leader, raising the bar for execution and engineering quality

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Staff Machine Learning Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Staff ML Engineerto lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 8–10+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

Why project44?  

At project44, we believe in better.  

We challenge the status quo because we know a better supply chain isn’t just possible—it’s essential. Better for our customers. Better for their business. Better for the world.  

With our Decision Intelligence Platform, Movement, we’re redefining how global supply chains operate. By transforming fragmented logistics data into real-time, AI-powered insights, we empower companies to connect instantly, see clearly, act decisively, and automate intelligently. Our Supply Chain AI enhances visibility, drives smarter execution, and unlocks next-gen applications that keep businesses moving forward.  

Headquartered in Chicago, IL with a 2nd HQ in Bengaluru, India we are powered by a diverse global team that is tackling the toughest logistics challenges with innovation, urgency, and purpose.  

If you’re driven to solve meaningful problems, leverage AI to scale rapidly, drive impact daily, and be part of a high-performance team – we should talk. 

Description:    

project44 is looking for a Senior Data Scientist to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing best-in-class integrations to accelerate how project44 connects to the world’s logistics networks.   

About the Role

• Senior Data Scientist to lead the development of next-generation AI/ML systems at Project44, spanning ETA, risk, anomaly detection, and supply chain intelligence. This role sits at the intersection of applied modeling, platform thinking, and production impact, with a mandate to both ship high-value ML capabilities and build reusable Data Science platform primitives that scale across teams.
• In addition, this role will drive the integration of Generative AI, LLMs, and agentic systems into core workflows—enabling reasoning-driven diagnostics, automation, and intelligent decision support across the supply chain.
• You will work closely with Data Science, ML Engineering, Data Engineering, Platform, and Product teams to deliver production-grade systems and establish a scalable, repeatable approach to AI development at P44.

What You’ll Do

• Drive High-Impact ML Systems Lead end-to-end development of models for ETA, risk, anomaly, and fraud—leveraging advanced techniques (embeddings, transformers, hybrid models).
• Build Data Science as a Platform Develop reusable ML infrastructure (features, experimentation, deployment, monitoring) to scale model development and reduce time-to-production.
• Lead GenAI & Agentic Systems Build LLM-powered solutions (RAG, diagnostics, automation, coding agents) and establish guardrails, evaluation, and explainability.
• Translate Business Problems into ML Solutions Convert customer workflows into well-defined ML problems and ensure measurable business impact.
• Drive Experimentation & Evaluation Establish strong offline/online evaluation frameworks tied to business outcomes.
• Collaborate Across Engineering Partner with MLE and DE to build scalable, reliable systems across the ML lifecycle.

What We’re Looking For

• Experience 5+ years in Data Science / Applied ML with a strong track record of building and deploying production-grade ML systems.
• Core Modeling & Technical Expertise Deep expertise across tree-based models, transformers, probabilistic modeling, and feature engineering, with a strong data-centric mindset.
• Data & Platform Fluency Proficient in SQL and Python, with hands-on experience in modern data platforms (Snowflake/Databricks), pipelines (Spark, Airflow), streaming systems (Kafka), and MLOps tooling.
• GenAI & LLM Capability Experience building RAG systems, working with embeddings and vector databases, and developing LLM-based applications and agentic workflows. Strong understanding of evaluation, guardrails, and safe deployment of GenAI systems.
• Systems & Engineering Mindset Familiarity with distributed systems, APIs, and deployment patterns, with the ability to write clean, production-quality code.
• Analytical Rigor & Diagnostics Strong ability to evaluate model performance, detect edge cases, run root cause analysis, and design robust monitoring and evaluation frameworks.
• Data Quality & Signal Awareness Experience handling messy, real-world data, including drift, bias, missingness, and anomalies, along with tools and techniques to detect and address these issues.
• Modeling Judgment & Trade-offs Ability to identify when to use ML versus heuristics and design pragmatic hybrid solutions. Strong understanding of architectural trade-offs across models and systems.
• Business Impact Orientation Clear understanding of how ML metrics translate to business outcomes, with the ability to balance trade-offs across accuracy, scalability, latency, and customer experience.
• Leadership & Communication Strong problem framing, stakeholder influence, and ability to communicate model behavior and decisions clearly to both technical and non-technical audiences. Proven track record of driving measurable business impact.

Preferred Skills

• Experience in logistics (Ocean, Truckload), supply chain, or high-volume operational systems
• Experience with geospatial data, routing, and tracking systems
• Experience with anomaly detection, fraud modeling, ETA prediction
• Experience building internal platforms or tools for DS teams

What Success Looks Like (6–12 Months)

• Deliver 2 high-impact ML capabilities with measurable customer value
• Establish standardized experimentation, monitoring, and RCA workflows
• Introduce GenAI/agentic capabilities that improve productivity and insight generation
• Reduce time-to-production and increase reuse across DS teams
• Drive measurable improvements in model performance and system reliability

In-office Commitment: This position requires a commitment to contribute to our collaborative culture by working in-office three days weekly. 

Diversity & Inclusion 

At project44, we're designing the future of how the world moves and is connected through trade and global supply chains. As we work to deliver a truly world-class product and experience, we are also intentionally building teams that reflect the unique communities we serve. We’re focused on creating a company where all team members can bring their authentic selves to work every day. 

We’re building a company that every one of us at project44 is proud to work for, and our journey of becoming a more diverse, equitable and inclusive organization, where all have a sense of belonging, is shaped through the actions of our leadership, global teams, and individual team members. We are resolute in our belief that each team member has an equal responsibility to mold and uphold our culture. 

project44 is an equal opportunity employer seeking to enrich our work environment by creating opportunities for individuals of all backgrounds and experiences to thrive. If you share our values and our passion for helping the way the world moves, we’d love to review your application! 

For any accommodation needed during the hiring process, please email   recruiting@project44.com. Even if you don’t meet 100% of the above job description you should still seriously consider applying. Studies show that you can still be considered for a role if you meet just 50% of the role’s requirements. 

More about project44 

Since 2014, project44 has been transforming the way one of the largest, most important global industries does business. As transportation and logistics continue to evolve and customer expectations around delivery become more demanding, industry technology must rise to the occasion. In just a few short years, we have created a digital infrastructure that eliminates the inefficiencies caused by dated technology and manual processes. Our Advanced Visibility Platform is used by the world’s leading brands to track shipments, collaborate with supply chain partners, drive operational efficiencies, and create outstanding customer experiences. 

About Us

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We're backed by Accel, Faction, NfX, Accomplice, and other top-tier investors.

Role Overview

OpenFX processes billions of dollars in transaction volume across global corridors. Every decision around pricing, risk, liquidity, reconciliation, and compliance depends on accurate, timely, and trustworthy data. We need Data Engineers who can build reliable data pipelines, ensure data correctness end to end, and make data usable for analytics, risk, and operations at scale. You will own critical data infrastructure that directly powers our financial operations.

Key Responsibilities

• Own 1 to 2 critical data pipelines that ingest, transform, and publish production data
• Design data models that are accurate, auditable, and easy to consume
• Build reliable ingestion pipelines from transactional systems and external partners
• Ensure data correctness and freshness through validation, monitoring, and backfills
• Handle late-arriving, duplicate, and inconsistent data safely
• Partner with Backend, Analytics, Risk, and Ops teams to translate requirements into robust data solutions
• Improve core data metrics such as pipeline reliability, data latency, and reconciliation accuracy
• Automate pipeline operations including retries, recovery, and backfills

What We're Looking For

Required

• 3 to 7 years experience in data engineering or backend data systems
• Strong SQL and data modeling fundamentals
• Experience building batch and/or streaming pipelines
• Experience working with relational databases and data warehouses
• Experience handling schema evolution and backfills
• Understanding of data quality, validation, and monitoring
• Ability to clearly explain data tradeoffs

Preferred

• Experience with Kafka, Spark, or Flink
• Experience with modern warehouses (BigQuery, Snowflake, Redshift)
• Experience with Airflow or similar orchestration tools
• Experience in fintech or regulated domains
• Familiarity with event-driven architectures
• Experience mentoring junior engineers

What We Offer

• Competitive salary and benefits package.
• Equity in a rapidly growing company.
• Opportunity to work in a fast-paced startup at the forefront of fintech innovation.
• Opportunity to make a significant impact on global financial infrastructure.
• Collaborative work culture with emphasis on personal and professional growth.

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

About Us

OpenFX is on a mission to move money as freely as data, unrestricted by time zones, banking hours, or legacy systems. We are building the infrastructure that will power the next generation of cross-border payment systems for institutions. The team's execution has been exceptional, and we're scaling at a remarkable pace. Our stellar early team comes with experience in companies like J.P. Morgan, Goldman Sachs, FalconX, Paypal, Affirm, Polygon, Kraken, Nium & others. We’re backed by Accel, Lightspeed, NfX and other top-tier investors.

Role Overview

We are seeking a talented Analytics Lead to build and lead our analytics function from the ground up. This role is crucial for establishing our core data infrastructure and delivering actionable insights across all teams to power strategic decision-making and drive business growth.

Key Responsibilities:

• Data Infrastructure & Governance:
  
  
• Design and implement our core analytics infrastructure, including data warehousing, ETL processes, and visualization tools.
• Establish data quality standards, automate routine reporting, and create self-service analytics tools to ensure data accuracy and accessibility.

• Business Intelligence & Insights:
  
  
• Create and maintain dashboards for key business metrics across operations, finance, partnerships, and growth teams.
• Develop comprehensive analytics for transaction monitoring, liquidity optimization, platform performance, and revenue forecasting.
• Analyze user behavior and transaction patterns to drive growth strategies.

• Risk & Financial Analytics:
  
  
• Build analytics models for pricing optimization and financial planning.
• Create risk monitoring systems and fraud detection analytics to ensure platform security.

• Strategic Partnership & Team Leadership:
  
  
• Partner with leadership to provide data-driven insights for strategic decision-making.
• Build, manage, and mentor a high-performing team of analysts as the organization scales.

What we are looking for

Must-haves:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
• 6+ years of experience in analytics or data science roles.
• Strong programming skills in Python and SQL.
• Experience with modern data stack tools (e.g., Snowflake, dbt, Airflow).
• Proven experience building and maintaining large-scale data pipelines.
• Excellent communication skills with the ability to present complex data to non-technical stakeholders.
• Strong problem-solving skills and meticulous attention to detail.

What helps you stand out:

• A Master's degree in a relevant field.
• Experience in a fintech or financial services environment.
• Direct experience with crypto/blockchain analytics.
• Startup experience is highly preferred.
• Expertise with data visualization tools like Tableau or Looker.

What We Offer

• Competitive salary and benefits package.
• Equity in a rapidly growing company.
• Opportunity to work in a fast-paced startup at the forefront of fintech innovation.
• Opportunity to make a significant impact on global financial infrastructure
• Collaborative work culture with emphasis on personal and professional growth.

We are committed to building a diverse and inclusive workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. 

JOB TITLE: Director of Product Management, Data & Analytics

LOCATION: Bangalore, India

REPORTS TO: Chief Product Officer

Th Role

TRG Screen is embarking on a strategic transformation of how data is accessed, consumed, and delivered across our product portfolio. Today, data lives within source and application databases — siloed, difficult to combine, and hard to expose to customers and internal teams. We are building a modern data lakehouse to change that, and we need a Director of Data Solutions to lead this journey.

This is a foundational, high-impact role. You will inherit a modern but underperforming data product, untangle legacy reporting built on stored procedures, and simultaneously set the vision and execution plan for the next generation of TRG Screen's data platform. You will serve as the senior data product leader for our product, engineering, and executive stakeholders.

This role is based in Bangalore, India, and begins as a senior individual contributor with a clear trajectory to build and lead a growing data product team.

Responsibilities

Stabilise & Improve the Current State

• Take ownership of our existing data product — assess gaps, stabilise performance, and deliver near- term improvements that create immediate value for customers and internal teams.
• Audit and rationalise a portfolio of legacy custom reports built on stored procedures — understand the business problems they solve, document them, and define a clear migration path.

Define the Data Lakehouse Vision

• Define the vision and roadmap for TRG Screen's data lakehouse, grounded in deep customer research and a clear understanding of where data solutions deliver the most value.
• Apply a Jobs to Be Done framework to uncover what customers are truly trying to accomplish and translate those insights into a prioritised product backlog.
• Conduct ongoing customer discovery with clients and customer-facing teams (Customer Success, Sales, Professional Services) to ensure the roadmap reflects real customer pain and opportunity.
• Work closely with the Data Architect and Database Engineer to communicate requirements clearly . You define the what and why; they own the how.
• Champion an AI-first approach to visualisation and insight delivery, evaluating and selecting third-party AI tooling rather than building bespoke visualisation layers.

Build & Deliver Data Products

• Define and ship customer-facing data products — including APIs, datasets, and consumption layers that customers or customer-serving teams directly use and derive value from.
• Productise TRG Screen's data as a revenue stream — define how data and APIs are packaged, tiered, and commercialised for customers and partners.
• In partnership with product stakeholders, own the API product strategy — defining APIs not just as technical interfaces but as sellable, scalable products with clear value propositions, entitlement models, and a developer experience that delights customers.
• Partner with engineering to translate customer-driven requirements into clear, actionable briefs.
• Ensure data quality, governance, reliability, and documentation across all data products.

Own the AI Data Strategy

• Serve as the product owner of TRG Screen's AI data foundation — defining what data needs to be available, in what form, and to what quality standard to power AI and ML workloads.
• Use customer research and Jobs to Be Done methodology to define intelligence layer product requirements; what AI-powered features and experiences customers need, handed off to technical teams for execution.
• Collaborate with TRG Screen's AI strategy stakeholders to align the data product roadmap with AI product priorities.
• Champion AI-first approaches to data consumption: evaluating and recommending AI-powered visualisation and insight tools.

Lead & Grow the Team

• Begin as a senior individual contributor with direct leadership responsibility — you will be the data product function at TRG Screen initially.
• Work in close partnership with a Database Engineer and Data Architect, providing product direction and prioritisation while they drive implementation.
• Build out your team as the platform matures, with a planned trajectory to hire and lead a Product Manager and Product Owner.
• Act as a player-coach: credible enough to go deep on architecture and technical decisions alongside engineering peers, while driving strategy and stakeholder conversations at the executive level.

Skills and Qualifications

Required Qualifications

• 8+ years of experience in data product management or related roles, with at least 3 years in a leadership capacity.
• Deep expertise in Jobs to Be Done and customer discovery — ability to uncover what customers truly need from data and translate that into a compelling product roadmap.
• Strong product instincts — knows how to prioritise ruthlessly, write clear requirements, and drive a backlog in an Agile environment.
• Solid working knowledge of data concepts (SQL, data modelling, APIs, ETL/ELT, BI tools), enough to be a credible partner to a Data Architect and Database Engineer.
• Experience defining and shipping data APIs as commercial products — including packaging, entitlements, and usage-based models.
• Understanding of data monetisation strategies — how to turn data assets into revenue-generating products.
• Strong understanding of AI and ML data requirements — how to define product needs for AI-powered features and intelligence layers.
• Familiarity with LLMs, generative AI, and AI-powered product surfaces — and how they consume and depend on structured, high-quality data.
• Strong stakeholder management skills — able to translate between engineering, product, and executive audiences.

Preferred Qualifications

• Familiarity with Power BI source integration or similar third-party BI connectivity.
• Exposure to AI-powered analytics or visualisation tooling.
• Experience with dbt, Airflow, or modern data orchestration tools.
• Background in a SaaS or multi-product environment where data is fragmented across systems.
• Prior experience in financial data, market data, or fintech — relevant to TRG Screen's domain

This is a hybrid role. At Bluevine, we pride ourselves on our collaborative culture, which we believe is best maintained through in-person interactions and a vibrant office environment. All of our offices have reopened in accordance with local guidelines, and are following a hybrid model. In-office days will be determined by location and discipline.

ABOUT THE ROLE:
We are seeking a high-caliber Python Engineer to architect the next generation of our business financing ecosystem. Joining a team defined by technical autonomy, you will specialize in evaluating and deploying cutting-edge, emerging technologies to ensure we are always utilizing the best-in-class stack for our business goals. This is a high-impact, hands-on role centered on designing and scaling production-grade infrastructure that powers our mission-critical backend systems and high-velocity data workflows.

WHAT YOU WILL DO:

• Build, evolve, and maintain machine learning infrastructure that powers Bluevine’s backend and data platforms
• Develop scalable infrastructure services in Python for production environments
• Work closely with data scientists and backend engineers to deliver reliable, high-performance solutions
• Use data and monitoring tools to improve availability, reliability, and sustainability of infrastructure
• Troubleshoot and optimize infrastructure components, including databases and distributed services

WHAT WE ARE LOOKING FOR:

• 5+ years of software development experience
• At least 2+ years of hands-on Python experience in production environments with AI first approach.
• Strong experience building and maintaining infrastructure services
• Experience working in cloud environments (preferably AWS)
• Solid understanding of production systems, scalability, and reliability
• Experience with data engineering tools (e.g. Spark, Kafka, Redshift,Airflow)
• Experience building and maintaining CI/CD and infrastructure pipelines (Docker, Airflow, Jenkins)
• Experience with AWS services.