Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.

Now, more than ever, the Toast team is committed to our customers. We’re taking steps to help restaurants navigate these unprecedented times with technology, resources, and community. Our focus is on building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love. And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that we’ll deliver on their needs for today while investing in experiences that will power their restaurant of the future. 

Bready* to make a change?

Toast is looking for a Staff Machine Learning Engineer to serve as a technical linchpin for our AI Platform team. At the P4 level, you aren't just deploying models; you are designing the fundamental infrastructure that enables dozens of teams to build, deploy, and monitor AI at scale. You will act as a force multiplier, mentoring senior engineers and setting the architectural standards for our MLOps lifecycle—from feature stores and automated retraining to high-performance inference at the edge.

About this Roll*:

• Architectural Leadership: Design and lead the evolution of a unified MLOps platform that supports diverse needs across Toast, ensuring high availability, scalability, and security of ML services.
• Engineering Excellence: Champion and institutionalize best practices for CI/CD for ML (MLOps), automated testing, and infrastructure-as-code (Terraform).
• Cross-Functional Synergy: Lead collaborative efforts across Data Engineering, DevOps, and Product teams to bridge the gap between model prototyping and production-grade reliability.
• Strategic Roadmapping: Partner with leadership and Product Managers to define the 1-2 year technical vision for AI infrastructure, prioritizing long-term stability over short-term fixes.
• Operational Ownership: Set the standard for observability and incident response for ML systems, driving root-cause analysis for complex system failures.
• Mentorship: Actively mentor P2 and P3 engineers, fostering a culture of technical rigor and continuous learning.

Do you have the right ingredients*?

• Education: Bachelor’s or Master’s degree in Computer Science, AI, or a related technical field.
• Experience: A minimum of 10-12+ years of professional software engineering experience, with at least 6-7 years specifically focused on productionizing and scaling ML systems at the enterprise level.
• Core Tech Stack: Expert-level proficiency in Python, Scala, or Java/Kotlin. Extensive experience with PySpark and high-performance computing.
• Generative AI & LLMOps: Proven track record of taking LLM applications from research to production, including experience with Vector Databases, LangChain/LangGraph, and A2A protocols.
• System Design: Superior ability to design distributed systems that handle millions of requests with sub-second latency.
• Experience with microservice based architecture, preferably with AWS tooling (SageMaker, DynamoDB, Athena, Glue, etc.)
• Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration, MLflow
• Profound knowledge of model deployment, orchestration (Apache airflow, Prefect), scaling, and managing CPU/GPU resources efficiently. 
• Exceptional problem-solving, analytical skills and the ability to tackle complex problems with a critical thinking approach. 
• Outstanding communication and interpersonal skills, coupled with a demonstrated ability to work collaboratively within a team environment.
• Foundational knowledge in statistical concepts (e.g. classification, regression, etc) and deep learning algorithms (e.g. CNN, RNN) is desirable

Bonus Ingredients (The "Staff" Edge)

• Data Strategy: Experience implementing enterprise-grade Feature Stores (e.g., Tecton, Feast) and real-time streaming frameworks like Apache Flink or Ray.
• Full-Stack Visibility: Ability to dive into the UI/UX layer (React) or deep into the kernel/networking layer to debug performance bottlenecks.

Open Source/Community: Contributions to relevant open-source projects (MLflow, Kubeflow, etc.) or a history of speaking at industry conferences.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy 
We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

• Design, deploy, and scale large-scale ML and data processing pipelines across cloud infrastructure.
• Build systems to ingest, process, and serve 250,000+ hours of multimodal data (video, audio, metadata).
• Architect and optimize GPU-based compute environments (e.g., NVIDIA Tesla clusters) for distributed training and inference.
• Develop high-throughput backend systems for video ingestion from desktop and mobile platforms.
• Implement distributed processing workflows, including job scheduling, fault tolerance, and resource allocation.
• Design and build human-in-the-loop and automated annotation systems to ensure data quality and scalability.
• Translate ML and multimodal research into scalable, production-grade cloud architectures.
• Optimize pipelines for performance, reliability, and cost efficiency across compute, storage, and networking layers.
• Collaborate with ML, data, and engineering teams to deliver end-to-end data workflows.

• 5+ years of experience in data engineering, ML pipelines, or distributed systems.
• Strong experience building scalable data pipelines for large datasets (video/audio preferred).
• Hands-on experience with cloud platforms (AWS, Azure, or GCP).
• Experience working with GPU-based environments and distributed computing.
• Strong programming skills in Python, Scala, or similar languages.
• Experience with data processing frameworks (Spark, Ray, Kafka, Airflow, or similar).
• Understanding of ML workflows, training pipelines, and inference systems.
• Experience designing fault-tolerant, high-availability systems.
• Strong knowledge of data storage systems (data lakes, object storage, distributed file systems).
• Ability to handle high-throughput, large-scale data ingestion and processing.

• Experience with multimodal AI (video, audio, NLP) systems.
• Familiarity with annotation tools and data labeling workflows.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Knowledge of cost optimization strategies for large-scale cloud workloads.

About the Role

This position exists to develop and enhance the customer onboarding experience and set up systems owned by the Customer Journey (CJ) team, within the Multi-Product Platform (MPP) division. The role plays a critical part in helping the team deliver on its mission: making POV (Proof of Value) onboarding smoother, faster, and increasingly self-serve. You will contribute directly to the backend systems that take enterprise customers from evaluation to full deployment, and help strengthen the team’s ability to deliver reliable, automated onboarding workflows at scale.

What you will do

Abnormal AI is looking for a driven and growth‑oriented Backend Software Engineer to join the Customer Journey (CJ) team. The team builds and maintains Abnormal’s customer onboarding and tenant management systems within the Multi-Product Platform (MPP) division. As a member of the team, you will build and scale backend services, contribute to automating manual steps in the onboarding process, and help decouple downstream systems from the onboarding pipeline. You’ll work across APIs, backend services, and data workflows to solve technical challenges related to large-scale customer provisioning at scale. We’re looking for candidates who are eager to learn, excited to work collaboratively, and motivated by building systems that directly impact how customers experience Abnormal.

Must Haves

• 2+ years of experience as a software engineer with a strong foundation in coding and problem-solving.
• 1+ years of hands-on experience in backend development using Python or Golang, with exposure to cloud-native environments.
• Solid understanding of databases, REST APIs, and data pipelines.
• Familiarity with LLMs and AI development tools such as Cursor, GitHub Copilot, or Claude.
• Experience working individually as well as in groups on a regular basis.
• Experience working with distributed teams, proficient in asynchronous and written communication.
• Experience building features and components from scratch and operating them, balancing feature development with operational tasks.

Nice to Haves

• Experience with Apache Airflow
• Familiarity with AWS services and deployment practices.
• Experience in building a feature or component from scratch

🚀 Ready to be part of AI transformation at Abnormal AI? Apply Now!

Once you apply, you’ll be invited to our AI-powered Development Challenge, where you’ll gain hands-on experience with AI-powered tools like Cursor and Copilot to build real-world application features. This challenge is a take-home assignment, requiring 2-4 hours of work to be completed within one week - apply when you’re ready!

#LI-UC1

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

As a global leader in Collaborative Work Management and with a market cap of $10bn we’ve experienced incredible growth in EMEA, expanding from 1 team and 3 engineers in 2018 to 9 teams with over 70 engineers in 2024. As we expand into India and build out a new operation, we're searching for a talented and motivated Principal Analytics Engineer (Data Architect) to serve as a thought leader in our data-driven decision-making. You will be responsible for the end-to-end system design and architecture of our business critical analytical systems (DWs). This role will be responsible for the design and development of a governed, reliable, and scalable analytics ecosystem, transforming raw data into high-value, performant data products for DS/ML, analytics, and reporting.

A key aspect of this role is providing thought leadership and architecting efficient, large-scale data transformation systems within Snowflake. You will have demonstrated experience architecting data solutions for SaaS companies, specifically within the Go-To-Market (GTM), Marketing, Customer Experience, and Financial business domains. Working as a strategic advisor to BI analysts, Data Scientists, and business leadership, you will drive the organization's data strategy, ensure data accessibility, and foster data democratization across the enterprise.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

• Lead the end-to-end system design and architecture for large, complex analytics systems, optimizing data transformations from our data lake in Snowflake into analytical data products (DWs).
• Define and drive the adoption of design standards, architectural principles, and data modeling methodologies (including Data Vault (DV 2.0) and dimensional modeling) across the organization.
• Propose and drive strategic initiatives and coordinate the technical roadmap for analytical systems across the engineering organization partnering closely with the Big Data Platforms (BDP) team.
• Serve as the data architect for critical SaaS business domains, including Go-To-Market, Marketing, Customer Experience, and Finance, translating ambiguous business problems into scalable technical analytical solutions.
• Develop and implement the organization's data strategy for data quality, observability, and testing, raising the bar for engineering quality.
• Architect and guide teams to build and maintain a governed, robust, reliable, and scalable analytics system leveraging Gen AI capabilities including AI-assisted code development practices.
• Act as a trusted advisor to BI analysts, data scientists, and business leaders, educating and advising leadership on technical data topics and data accessibility strategies.
• Foster data democratization via activation of data on critical platforms like Smartsheet Platform, Amplitude, ThoughtSpot, Gainsight & Salesforce.
• Actively mentor analytics engineers and provide mentorship across disciplines, leading forums such as guilds, design reviews, and engineering forums.
• Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

• 12+ years of experience in advanced data modeling, data architecture, and data warehousing. This role is expected to do development activities in combination of the data architecture scope, so hands-on experience is necessary.
• Deep expertise and 10+ years of hands-on experience with Data Vault (DV 2.0) and Dimensional Modeling.
• Expert-level knowledge of modern data stacks, including Snowflake, dbt, and data orchestration tools (e.g., Airflow, GitLab pipelines).
• Proven experience architecting and building analytical products for SaaS companies in GTM, Marketing, Customer Experience, and Financial data domains.
• Comprehensive understanding of data topologies (e.g., data mesh, hub/spoke) and data modeling methodologies (e.g., Data Vault, Kimball, Inmon).
• Demonstrated ability to drive clarity in ambiguous environments where the strategy may not be defined.
• Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
• Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
• Exceptional communication skills, with experience educating and advising senior leadership and mentoring teams across disciplines.
• Strong knowledge of data governance principles, CI/CD practices (e.g., GitLab), self-serve analytics tools (e.g., Amplitude, ThoughtSpot), and cloud architectures (AWS preferred).

Smartsheet is hiring a Senior Analytics Engineer to lead the way in data-driven decision-making. You will be responsible for the creation and maintenance of a governed, reliable, and scalable analytics system, transforming raw data into usable datasets for DS/ML, analytics, and reporting. 

A key aspect of this role is leading the architecture and implementation of efficient data transformation systems within Snowflake, fostering data democratization and impacting business outcomes. Working closely with BI analysts and Data scientists, you will ensure data accessibility and drive activation on critical customer-facing platforms.

This full-time position reports to the Director of Analytics Engineering and is based in Smartsheet’s corporate offices in Bengaluru, India.

You Will:

• Leading the implementation of efficient and scalable systems that optimize data transformations from our data lake in Snowflake into clean, documented data products. 
• Contribute to the design standards and architectural principle standards, designs and processes.
• Build and maintain a governed, robust, reliable, and scalable analytics system (DW/DV).
• Collaborating with BI analysts and data scientists to provide proper data accessibility guidelines.
• Foster data democratization via activation of data on critical platforms like Smartsheet platform, Amplitude, Thoughtspot , Gainsight.
• Create and contribute to frameworks that improve data quality and observability to identify and resolve issues faster.
• Create and implement data testing plans, encompassing data validation, data quality assessment, and regression testing, to identify anomalies, inconsistencies, or errors in produced datasets.
• Mentor and guide teams and help drive high standards across the team by conducting design reviews and engineering ideation forums.
• Collaborate with cross-functional teams to assess data privacy needs and define data masking strategies aligned with industry compliance standards (e.g., GDPR, HIPAA, CCPA).

You Have:

• 6+ years of experience in advanced data modeling using Data Vault (DV 2.0), dbt, and Snowflake.
• Proven experience in building analytics systems with data transformation, dependency, and workload management (Data Vault, AutomateDV, dbt core, Airflow, Snowflake, GitLab, SQL).
• Proven experience with building and maintaining business analytics layers and semantic layers to enable self-service for non-technical end-users.
• Strong production experience supporting and maintaining analytics/data warehouse solutions with mission-critical datasets.
• Familiarity with data governance principles for maintaining datasets to enable a single source of truth.
• Familiarity with self-serve product analytics tools (Amplitude, Thoughtspot, Tableau, Gainsight, etc.).
• Knowledge of code management and CI/CD practices (GitLab, Airflow, Snowflake, Terraform).
• Familiarity with AWS solutions such as S3, EC2, VPC.

Smartsheet is looking for an experienced Data Engineer to support and accelerate the productivity of our Go-To Market organization. In this role, you will work with Data Engineers to help build scalable and reliable data and reporting infrastructure. You will partner with Analytics decision-makers as part of a collaborative, motivated team. Your work will be instrumental in helping our Sales partners optimize their pipeline, increase retention, and close deals.

Our ideal candidate is curious and displays an ability to translate abstract data requests into actionable data solutions . To be successful in this role, you are able to communicate to a diverse audience of internal stakeholders. You should have strong technical acumen with data analytics tools and languages, the ability to identify areas of opportunity within the business, and build innovative solutions.

You Will:

• Help to create, evolve, and maintain the reporting infrastructure for the Sales organization to facilitate data across the organization
• Partner with engineering, data science, and other analytics teams to build scalable analytics solutions with a focus on reporting capabilities
• Mine large datasets to ensure data accuracy and completeness for reporting purposes   
• Analyze and monitor data for anomalies, with a focus on data quality and consistency within reports     
• Develop and maintain key performance indicators (KPIs) to track sales performance, pipeline health, and other critical metrics   
• Automate report generation and distribution to improve efficiency
• Provide technical expertise and guidance to junior analysts on data extraction, transformation, and loading (ETL) processes and reporting best practices
• Ensure data governance and data integrity across all reporting tools and platforms
• Proactively identify and propose improvements to existing reporting processes and systems
• Be a mentor and leader to the more junior analysts on the team
• Perform other duties as assigned

You Have:

• Bachelor's degree in a quantitative field (e.g. engineering, sciences, math, statistics, business, or economics)
• 5+ years of experience in an analytics/engineering role with increasing responsibility
• Experience in Cloud and SaaS go-to-market (GTM)
• Expertise in SQL and preparing data for analysis, modeling, and visualization
• 3+ years of experience using Python for data analysis / automation 
• 3+ years of experience with dbt core
• 3+ years of experience with Git (Gitlab, Github etc.) and CI/CD concepts like branching, merging, Code Reviews etc. 
• Demonstrated experience with a modern engineering tech stack (Airflow, AWS, Docker etc.) 
• Experience working with a business intelligence tool like Tableau, PowerBI, Looker, etc.

Nice To Have:

• Experience building ML models
• Proficiency with Tableau preferred
• Experience with statistics (time series analysis, cluster analysis, multivariate analysis)
• Experience publishing and presenting data and findings to executives and non-data users

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Principal Data & AI/ML Ops Engineers, who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform. 

You Will:

• Data Architecture and Design: Designing and overseeing the architecture of scalable and reliable data platforms, including data pipelines, storage solutions, and processing systems
• Data Modelling and Management:Developing and implementing data models, ensuring data quality, and establishing data governance policies
• Data Pipeline Development: Building and optimising data pipelines for ingesting, processing, and transforming large datasets from various sources
• Performance Optimisation: Identifying and resolving performance bottlenecks in data pipelines and systems, ensuring efficient data retrieval and processing
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Data Security and Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining data platform systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design involving large Petabytes of data with Databricks Lakehouse
• Experience in modern AI/Data infrastructure patterns, Semantics layer Organizing data for AI agents (metadata, context)
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python, SQL, and potentially Java or Scala
• Exposure to Snowflake and Data pipeline frameworks like Airbyte/Airflow is preferable
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Driving engineering excellence initiatives
• Legally eligible to work in India on an ongoing basis

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.
 

As Senior Analyst in our Model Risk Management team, you will help manage the Model Risk Program including completing model validation reviews, maintaining the model risk inventory, and monitoring model performance particularly for Fraud and Gen AI Models. You will work closely with the Data Science Team, architects, engineers and product managers to assess the risk of model design, implementation, and use across product lines.

A day in the life (Responsibilities) 

• Support the implementation and day-to-day execution of the Second Line of Defense (2LOD) Model Risk Management (MRM) program for high-risk models, with particular focus on Fraud detection models (Transaction Fraud & Merchant Fraud) and Generative AI / LLM-based systems deployed across Toast.
• Assist in maintaining and enhancing the Model Risk Management framework, including policies, procedures, validation standards, governance documentation, templates, and best practices aligned with evolving regulatory and industry expectations.
• Enforce model lifecycle standards across development, implementation, use, monitoring, recalibration, change management, governance, and decommissioning, ensuring appropriate controls for traditional ML models as well as GenAI systems (e.g., RAG architectures, copilots, AI-assisted decision tools).
• Contribute to the development, risk-tiering, and ongoing maintenance of a comprehensive model inventory, including assessment of model impact, intrinsic risk (complexity and methodology), reliance on model outputs, and emerging AI-specific risks.
• Perform independent model validation reviews under the guidance of senior leadership, covering conceptual soundness, data integrity, model methodology, performance metrics (e.g., AUC, precision/recall, calibration), stability, bias/fairness risk, explainability, and monitoring frameworks. Produce validation reports and track issue remediation plans through closure.
• For Fraud models, evaluate class imbalance handling, threshold optimization, cost-sensitive performance metrics, operational overlays, rule-based controls, and portfolio-level impact analyses.
• For Generative AI systems, validate systems and evaluate risks related to hallucination, prompt injection, adversarial vulnerabilities, data privacy and leakage, model explainability limitations, bias, guardrails, output monitoring, jailbreak testing, regression testing, and human-in-the-loop controls.
• Partner with Data Science, Data Engineering, Product/Engineering, Information Security, Legal/Compliance, Finance, Credit Risk and Business teams to obtain documentation, perform effective challenge, conduct validation and oversee performance monitoring
• Prepare reports and executive materials summarizing model risk issues, validation findings, monitoring insights, and remediation status for leadership review, risk committees, audit committees, and internal audit engagements.
• Research and stay informed on industry developments in fraud analytics, machine learning, Generative AI governance, and regulatory guidance (e.g., SR 11-7, OCC 2011-12, NIST AI RMF). Propose enhancements to strengthen Toast’s Model Risk and AI Governance framework.
• Contribute to the development of model risk training materials and support delivery of training sessions to key stakeholders to enhance awareness of fraud model risk and AI-related risks.
• Support ad-hoc initiatives related to model risk governance, AI oversight, regulatory compliance, and enterprise risk management enhancements.

What you'll need to thrive (Requirements)

• Advanced degree in Data Science, Statistics, Applied Mathematics, Computer Science, Engineering, or a related quantitative discipline
• 5+ years of relevant industry experience in Model Risk Management, Model Validation, Data Science, or Machine Learning within fintech, banking, payments, technology, or consulting environments, with exposure to fraud analytics, credit risk, or AI/ML model governance.
• Strong understanding of machine learning methodologies and statistical foundations, including model development, validation techniques, performance evaluation, calibration, and stability analysis.
• Hands-on experience with fraud detection models (e.g., transaction monitoring, chargeback prediction, merchant risk scoring) and familiarity with concepts such as class imbalance handling, threshold optimization, precision/recall trade-offs, and cost-sensitive evaluation.
• Familiarity with Generative AI and LLM-based systems (e.g., RAG architectures, embeddings, prompt engineering, AI copilots) and awareness of associated risks such as hallucination, bias, prompt injection, and data leakage.
• Strong proficiency in Python and SQL; experience with data science and ML tools such as Spark, scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Familiarity with software engineering best practices (version control, CI/CD, testing frameworks, Airflow, AWS or cloud platforms) is a plus.
• Knowledge of model risk management frameworks and regulatory guidance (e.g., SR 11-7, OCC 2011-12) and familiarity with emerging AI governance frameworks (e.g., NIST AI RMF) is highly desirable.
• Ability to translate complex quantitative methodologies into clear business insights and effectively challenge first-line model development teams while maintaining strong cross-functional partnerships.
• Demonstrated critical thinking, analytical rigor, and structured problem-solving skills, with the ability to manage multiple priorities and deliver high-quality outputs under tight deadlines.
• Excellent written and verbal communication skills, including experience drafting formal validation reports, executive summaries, and committee-level materials.

AI at Toast

At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.

Our Total Rewards Philosophy

We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits.

About the Team

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on experienced engineers to help us further our 24x7, global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.

About the Role

The Data User Platform and Programs team works at the intersection of data infrastructure, reliability, governance, developer tooling and AI systems, supporting thousands of internal data users including engineers, analysts, data scientists and business stakeholders.

This role is part of a founding engineering team in India, offering high ownership, strong growth opportunities, and direct influence over the platform’s long-term architecture. 

You will work on systems such as:

• Platform foundations for reliability, observability, cost-efficiency and compliance
• A unified data discovery and catalog experience
• AI-powered assistants and workflows for analytics and operations

You will collaborate closely with product managers, data engineers, and analytics teams to deliver solutions that reduce friction and increase trust across the data ecosystem.

You’re excited about this opportunity because you will…

• Improve scalability, performance, and reliability of data platform services through strong engineering practices
• Build and operate data discovery and metadata platforms that help users find the right datasets, dashboards, and metrics quickly and confidently
• Develop AI-enabled services and workflows, including self-serve tooling for creating, evaluating, and improving AI assistants
• Add observability, monitoring, and operational tooling to maintain platform SLAs and reduce incident response time
• Drive cost-efficient data platform design by identifying underutilized, redundant, or idle datasets, services, and compute resources
• Embed cost awareness into the data lifecycle, including:
• Designing systems that encourage reuse over duplication
• Instrumenting usage and cost signals into platform services
• Supporting safe deprecation and cleanup of stale data assets
• Partner with cross-functional teams in a fast-moving, product-driven environment

We’re excited about you because…

• B.E./B.Tech., M.E./M.Tech, or Ph.D. in Computer Science or equivalent
• 3+ years of experience with CS fundamental concepts and experience with at least one of the programming languages of Go, Java, and Python
• Prior technical experience in Big Data infrastructure, Cost Efficiency & Governance, you've built meaningful pieces of data infrastructure. Bonus if those were open-sourced technologies like Spark, Clickhouse, Iceberg and Airflow
• Experience improving efficiency, scalability, and stability of data platforms
• Experience building or operating backend systems in production environments

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. Team serves as the foundation for decision-making at DoorDash.

About the Role

DoorDash is looking for a Staff Software Engineer, Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs.

You’re excited about this opportunity because you will…

• Own critical data systems that support multiple products/teams
• Develop, implement and enforce best practices for data infrastructure and automation
• Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
• Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services
• Manage a portfolio of data products that deliver high-quality, trustworthy data
• Help onboard and support other engineers as they join the team

We’re excited about you because…

• 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects
• 6+ years experience working in data platform and data engineering or a similar role
• Proficiency in programming languages such as Python/Kotlin/Scala
• 4+ years of experience in ETL orchestration and workflow management tools like Airflow
• Expert in database fundamentals, SQL, data reliability practices and distributed computing
• 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kafka/Flink/Spark Streaming
• Excellent communication skills and experience working with technical and non-technical teams and knowledge of reporting tools 
• Comfortable working in fast paced environment, self starter and self organizing
• Ability to think strategically, analyze and interpret market and consumer information
• You must be located near one of our engineering hubs indicated above

We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on June 20, 2024.

Please see the independent bias audit report covering our use of Covey here.

About the Team

Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. Team serves as the foundation for decision-making at DoorDash.

About the Role

DoorDash is looking for a Software Engineer, Data to be a technical powerhouse to help us scale our data reliability, data infrastructure, automation and tools to meet growing business needs.

You’re excited about this opportunity because you will…

• Own critical data systems that support multiple products/teams
• Develop, implement and enforce best practices for data infrastructure and automation
• Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
• Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services
• Manage a portfolio of data products that deliver high-quality, trustworthy data
• Help onboard and support other engineers as they join the team

We’re excited about you because…

• 3+ years of professional experience
• 3+ years experience working in data platform and data engineering or a similar role
• Proficiency in programming languages such as Python/Kotlin/Scala
• 3+ years of experience in ETL orchestration and workflow management tools like Airflow
• Expert in database fundamentals, SQL, data reliability practices and distributed computing
• 3+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kafka/Flink/Spark Streaming
• Excellent communication skills and experience working with technical and non-technical teams and knowledge of reporting tools 
• Comfortable working in fast paced environment, self starter and self organizing
• Ability to think strategically, analyze and interpret market and consumer information
• You must be located near one of our engineering hubs indicated above

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on experienced engineers to help us further our 24x7, global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.

About the Role

The Data User Platform and Programs team works at the intersection of data infrastructure, reliability, governance, developer tooling and AI systems, supporting thousands of internal data users including engineers, analysts, data scientists and business stakeholders.

This role is part of a founding engineering team in India, offering high ownership, strong growth opportunities, and direct influence over the platform’s long-term architecture. 

You will work on systems such as:

• Platform foundations for reliability, observability, cost-efficiency and compliance
• A unified data discovery and catalog experience
• AI-powered assistants and workflows for analytics and operations

You will collaborate closely with product managers, data engineers, and analytics teams to deliver solutions that reduce friction and increase trust across the data ecosystem.

You’re excited about this opportunity because you will…

• Improve scalability, performance, and reliability of data platform services through strong engineering practices
• Build and operate data discovery and metadata platforms that help users find the right datasets, dashboards, and metrics quickly and confidently
• Develop AI-enabled services and workflows, including self-serve tooling for creating, evaluating, and improving AI assistants
• Add observability, monitoring, and operational tooling to maintain platform SLAs and reduce incident response time
• Drive cost-efficient data platform design by identifying underutilized, redundant, or idle datasets, services, and compute resources
• Embed cost awareness into the data lifecycle, including:
• Designing systems that encourage reuse over duplication
• Instrumenting usage and cost signals into platform services
• Supporting safe deprecation and cleanup of stale data assets
• Partner with cross-functional teams in a fast-moving, product-driven environment

We’re excited about you because…

• B.E./B.Tech., M.E./M.Tech, or Ph.D. in Computer Science or equivalent
• 6+ years of experience with CS fundamental concepts and experience with at least one of the programming languages of Go, Java, and Python
• Prior technical experience in Big Data infrastructure, Cost Efficiency & Governance, you've built meaningful pieces of data infrastructure. Bonus if those were open-sourced technologies like Spark, Clickhouse, Iceberg and Airflow
• Experience improving efficiency, scalability, and stability of data platforms
• Experience building or operating backend systems in production environments

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

About the Team

The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs, and is responsible for building internal data products that scale decision-making across business teams and drive efficiency in our operations. Data is fundamental to DoorDash’s success, and this team plays a critical role in enabling high-impact, data-driven solutions across Product, Operations, Finance, and more.

About the Role

As an Analytics Engineer, you’ll play a key role in building and scaling the data foundations that enable fast, reliable, and actionable insights. You’ll work closely with partner teams to drive end-to-end analytics initiatives; working alongside Data Engineers, Data Scientists, Software Engineers, Product Managers, and Operators.

This is a highly technical role where you'll be a driving force behind the analytics stack, delivering trusted data and metrics that support decision-making at all levels of the company. If you're energized by solving technical problems with data and comfortable being deeply embedded across several domains, this role is for you!

You’re excited about this opportunity because you will…

• Collaborate with data scientists, data engineers, and business stakeholders to understand business needs, and translate that scope into data requirements
• Identify key business questions and problems to solve for, and generate insights by developing structured solutions to resolve them
• Lead the development of data products and self-serve tools that enable analytics to scale across the company
• Build and maintain canonical datasets by developing high-volume, reliable ETL/ELT pipelines using data lake and data warehousing concepts
• Design metrics and data visualizations with dashboarding tools like Tableau, Sigma, and Mode
• Be a cross-functional champion at upholding high data integrity standards to increase reusability, readability and standardization

We’re excited about you because…

• 5+ years of experience working in business intelligence, analytics engineering, data engineering, or a similar role
• Strong proficiency in SQL for data transformation, comfort in at least one functional/OOP language such as Python or Scala
• Expertise in creating compelling reporting and data visualization solutions using dashboarding tools (e.g., Looker, Tableau, Sigma)
• Familiarity with database fundamentals (e.g., S3, Trino, Hive, Spark), and experience with SQL performance tuning
• Experience in writing data quality checks to validate data integrity (e.g., Pydeequ, Great Expectations)
• Excellent communication skills and experience working with technical and non-technical teams
• Comfortable working in fast fast-paced environment, self-starter, and self-organizer
• Ability to think strategically, analyze, and interpret market and consumer information

Nice to Have

• Experience with modern data warehousing platforms (e.g., Snowflake, Databricks, Redshift) and ability to optimize performance
• Experience building multi-step ETL jobs coupled with orchestrating workflows (e.g. Airflow, Dagster, DBT)
• Familiarity with experimentation concepts like A/B testing and their data requirements

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

CDP ETL & Database Engineer

The CDP ETL & Database Engineer will specialize in architecting, designing, and implementing solutions that are sustainable and scalable. The ideal candidate will understand CRM methodologies, with an analytical mindset, and a background in relational modeling in a Hybrid architecture.The candidate will help drive the business towards specific technical initiatives and will work closely with the Solutions Management, Delivery, and Product Engineering teams. The candidate will join a team of developers across the US, India & Costa Rica.

Responsibilities:

• ETL Development – The CDP ETL C Database Engineer will be responsible for building pipelines to feed downstream data They will be able to analyze data, interpret business requirements, and establish relationships between data sets. The ideal candidate will be familiar with different encoding formats and file layouts such as JSON and XML.
• Implementations s Onboarding – Will work with the team to onboard new clients onto the ZMP/CDP+ The candidate will solidify business requirements, perform ETL file validation, establish users, perform complex aggregations, and syndicate data across platforms. The hands-on engineer will take a test-driven approach towards development and will be able to document processes and workflows.
• Incremental Change Requests– The CDP ETL C Database Engineer will be responsible for analyzing change requests and determining the best approach towards implementation and execution of the This requires the engineer to have a deep understanding of the platform's overall architecture. Change requests will be implemented and tested in a development environment to ensure their introduction will not negatively impact downstream processes.
• Change Data Management – The candidate will adhere to change data management procedures and actively participate in CAB meetings where change requests will be presented and Prior to introducing change, the engineer will ensure that processes are running in a development environment. The engineer will be asked to do peer-to-peer code reviews and solution reviews before production code deployment.
• Collaboration s Process Improvement – The engineer will be asked to participate in knowledge share sessions where they will engage with peers, discuss solutions, best practices, overall approach, and The candidate will be able to look for opportunities to streamline processes with an eye towards building a repeatable model to reduce implementation duration.

Job Requirements:

• The CDP ETL & Database Engineer will be well versed in the following areas:
  • Relational data modeling.
  • ETL and FTP concepts.
  • Advanced Analytics using SQL Functions.
  • Cloud technologies - AWS, Snowflake.
• Able to decipher requirements, provide recommendations, and implement solutions within predefined.
• The ability to work independently, but at the same time, the individual will be called upon to contribute in a team setting.
• The engineer will be able to confidently communicate status, raise exceptions, and voice concerns to their direct manager.
• Participate in internal client project status meetings with the Solution/Delivery management.
• When required, collaborate with the Business Solutions Analyst (BSA) to solidify.
• Ability to work in a fast paced, agile environment; the individual will be able to work with a sense of urgency when escalated issues arise.
• Strong communication and interpersonal skills, ability to multitask and prioritize workload based on client demand.
• Familiarity with Jira for workflow , and time allocation.
• Familiarity with Scrum framework, backlog, planning, sprints, story points, retrospectives.

Required Skills: 

• ETL – ETL tools such as
  • Talend (Preferred, not required)
  • DMExpress – Nice to have
  • Informatica – Nice to have
• Database - Hands on experience with the following database Technologies
  • Snowflake (Required)
  • MYSQL/PostgreSQL – Nice to have
  • Familiar with NOSQL DB methodologies (Nice to have)
• Programming Languages – Can demonstrate knowledge of any of the
  • PLSQL
  • JavaScript Strong Plus
  • Python - Strong Plus
  • Scala - Nice to have
• AWS – Knowledge of the following AWS services:
  • S3
  • EMR (Concepts)
  • EC2 (Concepts)
  • Systems Manager / Parameter Store
• Understands JSON Data structures, key value
• Working knowledge of Code Repositories such as GIT, Win CVS,
• Workflow management tools such as Apache Airflow, Kafka, Automic/Appworx
• Jira

Minimum Qualifications: 

• Bachelor's degree or equivalent.
• 4+ Years' experience.
• Excellent verbal C written communications skills.
• Self-Starter, highly motivated.
• Analytical mindset.

Company Summary:

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/2024/06/1G/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/20240G04622808/en/Zeta-Increases-3Q%E2%80%GG24-

Guidance

https://www.prnewswire.com/news-releases/zeta-global-opens-ai--data-labs-in-san-francisco-and-nyc- 300S45353.html

https://www.prnewswire.com/news-releases/zeta-global-recognized-in-enterprise-marketing-software-and-   cross-channel-campaign-management-reports-by-independent-research-firm-300S38241.html

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.

 Marketing Solutions Developer

Job Description

The type of profile that would be required to fulfil this role is outlined below for a ##role name## with approximately 3 years of experience delivering personalised and interactive web experiences. This role sits at the intersection of front-end development and marketing technology, requiring strong JavaScript capabilities to enhance, customise, and troubleshoot dynamic web components integrated with marketing platforms.

The role will work on a variety of personalised web experiences including form customisation, dynamic content loading, API integrations, and behaviour overrides — using JavaScript as the primary tool to solve problems and implement creative solutions.

Key Responsibilities:

JavaScript-Driven Web Personalisation:

• Build and extend interactive web pop-ins using JavaScript in personalisation tools (e.g., Digioh).
• Override default form behaviour to support dynamic functionality like expiry timers, conditional rendering, and score-based image swapping.
• Parse encrypted query parameters and tokens to personalise landing page content.
• Incorporate third-party or remote data (e.g., dealer lists, product lookups) into forms via asynchronous JavaScript.
• Implement client-side tracking and event submission using custom JS logic in coordination with personalisation tags (e.g., P13n).

API & Integration Work:

• Fetch and handle remote data using RESTful APIs within JavaScript-driven experiences.
• Work with JSON payloads to populate form elements and build dynamic UI elements.
• Bridge the gap between client CRM systems and the Zeta platform using front-end scripting where required.

Technical Troubleshooting & Investigations:

• Debug issues with form behaviour, lead delivery failures, or API responses using browser developer tools and techniques such as network inspection and console logging.
• Investigate and resolve anomalies in dynamic rendering, scoring logic, and tag-based tracking mechanisms.
• Assess new or unsupported client requirements and devise feasible JavaScript-based workarounds.

Required Skills & Experience:

• 3+ years’ hands-on experience in front-end development with a strong focus on JavaScript
• Deep understanding of JavaScript (ES6+), including async/await, event handling, DOM manipulation, and browser APIs
• Experience integrating with REST APIs and handling authentication, error states, and data formatting
• Solid HTML and CSS skills for customising and styling interactive components
• Familiarity with browser dev tools (Chrome/Edge) for inspecting issues and testing scripts
• Experience implementing custom business logic into web forms and overlays (e.g., Digioh or similar platforms)

Desirable Skills:

• Experience using JavaScript in a marketing context: web personalisation, form tracking, user targeting
• Exposure to customer data platforms or marketing automation tools (e.g., Zeta Marketing Platform, Adobe Target, etc.)
• Experience mediating API interactions via orchestration tools (e.g., Airflow) or writing client-side logic to handle fallback flows
• Knowledge of encoding/decoding encrypted query strings and URL-safe tokens
• Familiarity with campaign-based tools like Push Planet or CMS-driven landing pages

Soft Skills:

• Strong problem-solving skills and self-starting attitude
• Ability to balance technical perfection with pragmatic delivery
• Clear communicator, comfortable writing handovers and technical notes
• Willingness to dive into ambiguous requirements and turn them into structured, testable solutions
• Team player comfortable collaborating with cross-functional teams (e.g., delivery, campaign ops, technical account managers)

Company Summary:

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

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.

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. 

About the role

We are seeking an accomplished Data Engineer to join our dynamic and rapidly expanding Tech Ops division. With significant projected growth, this is an opportunity to drive meaningful technical impact. In this role, you will work directly with customers, data vendors, and internal engineering teams to design, implement, and optimize complex data integration solutions within a modern, large‑scale cloud environment.

You will leverage advanced skills in distributed computing, data architecture, and cloud-native engineering to enable scalable, resilient, and high‑performance data ingestion and transformation pipelines. As a trusted technical advisor, you will guide customers in adopting Abacus’s core data management platform and ensure high-quality, compliant data operations across the lifecycle.

Your day to day

• Architect, design, and implement high-volume batch and real-time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks.
• Build end‑to‑end ingestion frameworks integrating with Databricks, Snowflake, AWS services (S3, SQS, Lambda), and vendor data APIs, ensuring data quality, lineage, and schema evolution.
• Develop data modeling frameworks, including star/snowflake schemas and optimization techniques for analytical workloads on cloud data warehouses.
• Lead technical solution design for health plan clients, creating highly available, fault-tolerant architectures across multi-account AWS environments.
• Translate complex business requirements into detailed technical specifications, engineering artifacts, and reusable components.
• Implement security automation, including RBAC, encryption at rest/in transit, PHI handling, tokenization, auditing, and compliance with HIPAA and SOC 2 frameworks.
• Establish and enforce data engineering best practices, such as CI/CD for data pipelines, code versioning, automated testing, orchestration, logging, and observability patterns.
• Conduct performance profiling and optimize compute costs, cluster configurations, partitions, indexing, and caching strategies across Databricks and Snowflake environments.
• Produce high-quality technical documentation including runbooks, architecture diagrams, and operational standards.
• Mentor junior engineers through technical reviews, coaching, and training sessions for both internal teams and clients.

What you bring to the team

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field.
• 7+ years of hands‑on experience as a Data Engineer working with large‑scale, distributed data processing systems in modern cloud environments.
• Working knowledge of U.S. healthcare data domains—including claims, eligibility, and provider datasets—and experience applying this knowledge to complex ingestion and transformation workflows.
• Strong ability to communicate complex technical concepts clearly across both technical and non‑technical stakeholders.
• Expert‑level proficiency in Python, SQL, and PySpark, including developing distributed data transformations and performance‑optimized queries.
• Demonstrated experience designing, building, and operating production‑grade ETL/ELT pipelines using Databricks, Airflow, or similar orchestration and workflow automation tools.
• Proven experience architecting or operating large‑scale data platforms using dbt, Kafka, Delta Lake, and event‑driven/streaming architectures, within a cloud‑native data services or platform engineering environment—requiring specialized knowledge of distributed systems, scalable data pipelines, and cloud‑scale data processing.
• Experience working with structured and semi‑structured data formats such as Parquet, ORC, JSON, and Avro, including schema evolution and optimization techniques.
• Strong working knowledge of AWS data ecosystem components—including S3, SQS, Lambda, Glue, IAM—or equivalent cloud technologies supporting high‑volume data engineering workloads.
• Proficiency with Terraform, infrastructure‑as‑code methodologies, and modern CI/CD pipelines (e.g., GitLab) supporting automated deployment and versioning of data systems.
• Deep expertise in SQL and compute optimization strategies, including Z‑Ordering, clustering, partitioning, pruning, and caching for large‑scale analytical and operational workloads.
• Hands‑on experience with major cloud data warehouse platforms such as Snowflake (preferred), BigQuery, or Redshift, including performance tuning and data modeling for analytical environments.

What we would like to see but not required:

• Experience in large-scale healthcare or payer data environments.

What you’ll get in return :

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements :

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About Us

“Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. 

WHY JOIN CAPCO?

You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry.

MAKE AN IMPACT

Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services.

#BEYOURSELFATWORK

Capco has a tolerant, open culture that values diversity, inclusivity, and creativity.

CAREER ADVANCEMENT

With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands.

DIVERSITY & INCLUSION

We believe that diversity of people and perspective gives us a competitive advantage.

MAKE AN IMPACT

Role: GCP Data Engineer 

Job Summary:

We are looking for an enthusiastic GCP Data Engineer to join our dynamic and growing project team. In this role, you will have the opportunity to develop your skills while contributing to large-scale data projects on Google Cloud Platform. You will work closely with senior engineers and data analysts to build and maintain robust data pipelines, helping to turn raw data into actionable insights. This is an excellent opportunity for a foundational career in data engineering within a supportive and collaborative environment.

Key Responsibilities:

· Develop, test, and maintain data pipelines and ETL/ELT processes using Python, SQL, and GCP services.

· Write and optimize complex SQL queries in BigQuery for data transformation, extraction, and analysis.

· Assist in the design and implementation of data models within our data warehouse.

· Collaborate with the broader project team to understand data requirements and deliver effective solutions.

· Troubleshoot and resolve issues in data pipelines and data quality to ensure accuracy and availability.

· Contribute to documentation and adhere to data engineering best practices.

· Support the team in various data-related tasks and be eager to learn new technologies and techniques.

Required Qualifications:

· Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.

· 5-8 years of hands-on experience with strong programming skills in Python for data manipulation and processing.

· Proficiency in SQL for querying and data transformation.

· Hands-on experience or significant project work with Google Cloud Platform (GCP).

· Familiarity with core GCP data services, particularly BigQuery and Pub/Sub.

· Strong understanding of data warehousing concepts and ETL/ELT processes.

· A proactive and curious mindset with strong problem-solving skills.

· Excellent communication and teamwork skills, with the ability to work effectively in a large project team.

Preferred Qualifications:

· Experience with other GCP services such as Cloud Composer (Airflow) or Dataflow, Cloud Functions.

· Familiarity with version control systems, especially Git.

· Google Cloud certification (e.g., Associate Cloud Engineer) is a plus.

· A passion for data and a strong desire to grow a career in the data engineering field.

THE ROLE

We are seeking a highly skilled and hands-on Senior Finance Data & Analytics Engineer (IC role) to lead the design and development of the Finance Data Cube, enabling enterprise-wide insights into Customer Lifetime Value (CLTV), Contribution Margin, and other key financial metrics.

WHAT YOU'LL DO

• Design, build, and own the Finance Data Cube, integrating financial, customer, and operational datasets.
• Model data to support CLTV, Contribution Margin, and other profitability KPIs across multiple dimensions (customer, product, LOB, geography, etc.)
• Be a data architect for Finance , bring different data into cohesive and answer critical questions
• Leverage AI tools to automate data summarization, anomaly detection, and narrative insights for Finance stakeholders.
• Scale data infrastructure to support large volumes and complex financial models.
• Build and manage Semantic Layer models to standardize business metrics and enable self-serve analytics
• Translate complex financial concepts and KPIs into scalable, maintainable data models.
• Implement strong controls for data quality, lineage, and governance.
• Maintain clear documentation of data transformations, metric definitions, and AI model logic.
• We are primarily an in-office environment and therefore, you will be expected to work from the Bangalore office in compliance with Pure’s policies, unless you are on PTO, or work travel, or other approved leave.

WHAT YOU BRING

• Experience: 8+ years in Finance Data Engineering, FP&A Analytics, or Financial Systems, with exposure to AI/ML-based analytics(added advantage)
• Proficiency with Snowflake and modern data stacks with strong SQl and data modeling expertise 
• Deep understanding of finance data set , SAP , Contribution margin, CLTV would be an added advantage
• Experience with data orchestration tools (Airflow, dbt) and tableau platform
• Hands-on experience with Python, PySpark, or R for automation and model integration.
• Proven ability to translate financial logic into scalable data models.
• Experience in Cortex Analyst/Search components to enable AI/ML-driven insights, natural language querying, and intelligent data discovery is preferred. 
• Knowledge of predictive modeling, time-series forecasting, and generative AI in analytics.
• Ability to evaluate and apply AI responsibly in financial contexts.

 #LI-ONSITE

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

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

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

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data. Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands—across multiple industries around the globe—rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We are always looking to “Simplify and Share” our knowledge when we collaborate to remove obstacles for each other. We hold ourselves accountable for our actions and outcomes and strive for excellence. We “Own It”. Every day, we innovate and evolve, so that today is “Always Better Than Yesterday”. If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture and our people. Reltio was founded on a distributed workforce and offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology where your desire to be part of a collaborative team is met with a laser-focused mission to enable digital transformation with connected data, let’s talk!

About the Role

We are seeking a Senior AI Engineer with a strong foundation in Python capabilities, and hands-on experience building Agentic AI applications that integrate with Large Language Models (LLMs) Large Language Models (LLMs). We are also looking for him to be a full-stack Engineer with hands-on experience with mobile front-end hands-on experience with mobile front-end Flutter, React-native. This role blends traditional backend engineering expertise with next-generation AI agentic systems development, requiring not just system design skills, but also creativity in prompt engineering, AI product development and working with data-rich environments.

You will contribute to the design and implementation of intelligent backend services that coordinate LLMs, agents, and data workflows to support enterprise-grade agentic systems.

Key Responsibilities

• Develop robust, scalable Java/Python based backend systems that enable the orchestration of Agentic AI workflows.
• Develop state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
• Integrate LLMs (e.g., OpenAI, Mistral, Claude, LLaMA) into backend pipelines to power autonomous or semi-autonomous decision-making.
• Hands on experience with mobile front-end Flutter, React-native etc.
• Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
• Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
• Work closely with various stakeholders to design agent architectures and LLM toolchains (using frameworks like LangGraph, Crew AI, AutoGen, etc.).
• Implement services and APIs that manage prompt chaining, tool invocation, and contextual memory for agents.
• Collaborate with data engineers to ensure clean, efficient, and real-time access to structured and semi-structured data.
• Apply prompt engineering best practices to improve agent behavior, task accuracy, and adaptability.
• Monitor and optimize service performance, reliability, and scalability in production environments.
• Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
• Contribute to code reviews, mentoring, and best practices for hybrid backend/AI development.

Required Qualifications

• 5+ years of overall experience mobile front-end Flutter, React-native etc
• 2+ years of experience in developing and deploying machine learning models and AI products in production environments.
• Experience in Agentic AI systems development using tools such as LangGraph, Crew AI, AutoGen, or similar.
• Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
• Experience integrating or orchestrating LLMs within business workflows or intelligent assistants.
• Solid understanding of prompt engineering techniques (e.g., system messages, chaining, tool invocation prompts).
• Familiarity with data engineering concepts, including pipelines, data models, and ETL workflows.
• Strong grasp of object-oriented design, data structures, and algorithms.

Preferred Qualifications

• Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex, RAG pipelines).
• Background in building microservices or backend systems for data-rich AI/ML platforms.
• Experience with vector databases, embedding services, or semantic search integration.
• Knowledge of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and DevOps best practices.
• Experience in developing LLM-powered agents, copilots, or task bots.

What We Offer

• Opportunity to work on cutting-edge backend and AI systems, including agentic automation and LLM innovation.
• A flexible hybrid work model in our Bangalore office.
• Competitive compensation with performance-based rewards.
• A culture that promotes engineering excellence, experimentation, and growth.Access to learning platforms, technical workshops, and industry-leading AI research.

Why Join Reltio?*

• Health & Wellness:
  • Comprehensive Group medical insurance including your parents with additional top-up options.
  • Accidental Insurance
  • Life insurance
  • Free online unlimited doctor consultations
  • An Employee Assistance Program (EAP)
• Work-Life Balance:
  • 36 annual leaves, which includes Sick leaves – 18, Earned Leaves - 18
  • 26 weeks of maternity leave, 15 days of paternity leave
  • Very unique to Reltio - 01 week of additional off as recharge week every year globally
• Support for home office setup:
  • Home office setup allowance.
• Stay Connected, Work Flexibly: Mobile & Internet Reimbursement
• No need to pack a lunch—we’ve got you covered with a free meal.And many more…..

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.

The Community You Will Join:

The Guest & Host team based out of India, operates to ensure high quality supply and merchandising differentiates our brand, by providing tools to be used by 1000+ operations agents for supply vetting and quality moderation. As Airbnb expands beyond the core, it is looking to onboard supply outside of the core stays business which requires enhancing our tools. The operational tasks we face are diverse and rapidly evolving. The current manual processes and lack of optimum tooling capabilities hinder the ability of operation agents to work more efficiently, maintain business continuity, and achieve higher scale. 

The Difference You Will Make:

As a Data Engineer on the Guest & Host team, you will play a pivotal role in shaping the systems that onboard and manage the highest quality supply across Airbnb. You’ll build robust data pipelines and platforms that power end-to-end visibility for supply operations, from onboarding and regulatory compliance to AI-assisted vetting and listing quality enforcement. Your work will directly enable operations, product, and ML teams to scale trusted supply globally, ensuring every home, service, and experience meets Airbnb’s standards. Whether it’s surfacing insights to optimize onboarding flows, enabling smarter audit triggers, or supporting nuanced licensing workflows, your contributions will be foundational to helping hosts join Airbnb efficiently and ensuring guests have access to safe, high-quality stays.
As you build and maintain key components of the critical data ecosystem, you’ll have the opportunity to contribute to creating standards and best practices for Airbnb’s Data Engineering. Your work on solving complex business challenges at scale will be instrumental in shaping the tools, processes, and standards used by the broader data community.

A Typical Day:

• Design, build, and maintain robust and efficient data pipelines that collect, process, and store data from various sources, including user interactions, listing details, and external data feeds.
• Develop data models that enable the efficient analysis and manipulation of data for merchandising optimization. Ensure data quality, consistency, and accuracy.
• Build scalable data pipelines (SparkSQL & Scala) leveraging Airflow scheduler/executor framework
• Collaborate with cross-functional teams, including Data Scientists, Product Managers, andSoftware Engineers, to define data requirements, and deliver data solutions that drive merchandising and sales improvements.
• Contribute to the broader Data Engineering community at Airbnb to influence tooling and standards to improve culture and productivity
• Improve code and data quality by leveraging and contributing to internal tools to automatically detect and mitigate issues

Your Expertise:

• 6+ years of relevant industry experience 
• BE/B.tech in computer science or relevant technical field
• Extensive experience designing, building, and operating robust distributed data platforms (e.g., Spark, Kafka, Flink, HBase) and handling data at the petabyte scale.
• Strong knowledge of Java, Scala, or Python, and expertise with data processing technologies and query authoring (SQL).
• Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions
• Expertise with ETL schedulers such as Apache Airflow, Luigi, Oozie, AWS Glue or similar frameworks
• Solid understanding of data warehousing concepts and hands-on experience with relational databases (e.g., PostgreSQL, MySQL) and columnar databases (e.g., Redshift, BigQuery, HBase, ClickHouse)
• Excellent written and verbal communication skills

G-P helps organizations build global teams in minutes, not months. As part of this mission, we’ve created an indispensable AI agent for HR leaders, G-P Gia™ .

Gia is our AI-powered global HR agent that provides HR compliance guidance instantly. Built on over a decade of global employment and legal expertise and 100,000+ vetted articles, Gia analyzes and generates compliant documents and delivers the answers that HR leaders trust — reducing reliance on outside legal counsel and cutting compliance costs by up to 95%.

About The Position:

We’re building GIA — AI for General Counsel, in-house legal teams, and HR teams. GIA is a startup that demands extreme ownership, relentless execution, and zero tolerance for waiting on someone else to make the call. This role sits at the intersection of data science, data engineering, and product analytics. You build the pipelines, run the analysis, train the models, and — most importantly — tell us what the data means for the product. Not dashboards for the sake of dashboards. Insights that change what we build next.

What You Will Do:

• Build and own data infrastructure — pipelines, warehousing, ETL/ELT, data quality; make sure the foundation is solid
• Analyze product usage and user behavior — identify patterns, segment users, surface what matters from the noise; think like a product person, not just a data person
• Build models that ship — LLM-based systems, traditional ML (classification, clustering, NLP), evaluation frameworks; whatever the problem needs
• Define and track the metrics that matter — activation, retention, engagement, PQLs; connect data to product and GTM decisions
• Run experiments and measure impact — A/B tests, causal analysis, cohort studies; rigorous but fast
• Turn data into product conviction — you don’t just hand off charts, you tell the team what to do and why

What We Are Looking For:  

Minimum Requirements: 

• 5+ years across data science, data engineering, and analytics — you do all three, not just one
• Strong SQL and Python — complex queries, data modeling, scripting, analysis; this is your daily toolkit
• Databricks or equivalent modern data platform experience (Snowflake, BigQuery)
• LLM experience — fine-tuning, prompt engineering, embeddings, RAG, evaluation; not just API calls
• Traditional ML depth — classification, regression, clustering, NLP, feature engineering; you pick the right tool for the problem
• Product mindset — you filter signal from noise, understand user behavior, and connect analysis to product decisions
• Pipeline engineering — you build reliable, scalable data pipelines, not notebooks that break in production
• Clear communicator — you present findings to non-technical stakeholders with clarity and conviction

Preferred Qualifications: 

• Experience at an early-stage startup or as a founding data hire
• Built product analytics from scratch — instrumentation, event taxonomy, dashboards, self-serve reporting
• Legal or HR domain experience
• Experience with LLM evaluation and observability (tracing, scoring, drift detection)
• Familiar with dbt, Airflow/Dagster, Spark, or similar orchestration and transformation tools

How we evaluate

• Give you a real dataset and ask what you’d do with it — we want product thinking, not just technical chops
• Walk us through a time your analysis changed a product decision
• Design a data pipeline or model architecture on the whiteboard
• Show us how you’d instrument and measure a new feature from scratch

Interested? Reach out with an example of an insight you uncovered that changed what a team built.

Simtra BioPharma Solutions (Simtra) is a world-class Contract Development Manufacturing Organization, partnering with pharmaceutical and biotech companies to bring their sterile injectable products to market. With facilities in Bloomington, Indiana, US and Halle/Westfalen, Germany, we offer a wide range of delivery systems including pre-filled syringes, liquid/lyophilized vials, diluents for reconstitution, powder-filled vials and sterile crystallization.  

Our product types include biologics and small molecules, cytotoxics, highly potent compounds, diluents for reconstitution and vaccines – which are all directly injected into patients worldwide.  As such, there is a strong emphasis on quality and continuous improvement at Simtra.  We hold ourselves to the highest quality and regulatory standards.

While our primary focus is cGMP manufacturing, we offer many support services including formulation and development, lyophilization optimization, global regulatory support and secondary packaging.  Our teams are driven to help clients scale, innovate and bring life-changing medicines to patients worldwide.

Why join Team Simtra? Because we:

Make it HAPPEN – We bring a growth mindset to every opportunity, developing new skillsets and exceeding our expectations and those of our customers.

Make it TOGETHER – We work as one, respecting each voice and tapping into our unique strengths across teams—so we can solve problems in new ways.

Make it RIGHT – We hold ourselves to a high standard of excellence, fulfilling our commitments to the customer, their patients, and our team members.

Make it COUNT – We take pride in our day-to-day work, knowing the impact we make – taking on challenges big and small to improve patient health.

This role:

The Validation Lead/Associate III, Commissioning Qualification, Validation is a strong individual contributor within the Validation and Qualification Department. This position oversees and executes equipment FAT, SAT, IQ, OQ, PQ activities along with validation and documentation activities. In addition, it includes contribution roles within Sterility Assurance and Cleaning Validation. This position reports to the Sr. Manager, Technical Services.

Responsibilities:

• Provide guidance, support, direction, and leadership through positive interaction with all personnel during daily operations.
• Represents CQV in internal, client, and regulatory audits as needed.
• Develops procedures and supports the facility equipment qualification and validation program.
• Conducts or coordinates performance qualification execution for new products.
• Maintain and generate accurate and complete records, reports and documentation as required for summary preparation.
• Makes process improvements and modifications to the validation program as needed.
• Initiates and drives change controls (CCM).
• Review and approve Master Batch Records, Master Specification Sheets, Line Manufacturing Records and Bill of Materials.
• Author and approve qualification and validation documents
• Attend Equipment FAT, including international travel as required.
• Leads and participates in planned maintenance activities, including HEPA certification and visual airflow testing (smoke testing).

 Requirements (Education and Experience):

• Bachelor’s degree required, preferably in a science or technical area
• Minimum of 2 years related experience required, preferably 2 years supervisory experience.
• Computer proficiency in Microsoft Word, Excel, and Outlook and the ability to use enterprise software (examples include: JDE, BPLM, Pilgrim, Trackwise, etc.)
• Self-directed with high initiative and ownership
• Critical thinking, creative thinking, and problem solving skills

Physical / Safety Requirements:

• Ability to meet Grade C and D gowning requirements.
• Duties will require overtime work, including nights and weekends.
• Use of hands and fingers to manipulate equipment is required.
• Position requires standing for long hours, but may involve walking or sitting for periods of time.

In return, you’ll be eligible for[1]:

• Day One Benefits
  • Medical & Dental Coverage
  • Flexible Spending Accounts
  • Life and AD&D Insurance
  • Supplemental Life Insurance
    • Spouse Life Insurance
    • Child Life Insurance
  • 401(k) Retirement Savings Plan with Company Match
  • Time Off Program
    • Paid Holidays
    • Paid Time Off
    • Paid Parental Leave and more
  • Adoption Reimbursement Program
  • Education Assistance Program
  • Employee Assistance Program
  • Community and Volunteer Service Program
  • Employee Ownership Plan
• Additional Benefits
  • Short and Long-Term Disability Insurance
  • Voluntary Insurance Benefits
    • Vision Coverage
    • Accident
    • Critical Illness
    • Hospital Indemnity Insurance
    • Identity Theft Protection
    • Legal and more
  • Onsite Campus Amenities
    • Workout Facility
    • Cafeteria
    • Credit Union

[1] Current benefit offerings are in effect through 12/31/26

Disclaimer

This job description is intended to provide the minimum knowledge, skills and abilities necessary to perform the job.  It may not be inclusive of all the duties and responsibilities of the job.  Simtra reserves the right to make modifications based on business requirements.

Equal Employment Opportunity

Simtra is proud to be an equal opportunity employer. Simtra evaluates qualified applicants without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, protected veteran status, disability/handicap status or any other legally protected characteristic.

Data Privacy

To learn more about Simtra's approach to data privacy, please review the Simtra Recruitment Platform Global Privacy Policy:  https://simtra.com/privacy-policy/

Senior Database Engineer III (MySQL) – Production Reliability & Platform Engineering

Location : Bangalore

Work Timings: 2 PM to 11 PM IST

LivePerson (NASDAQ: LPSN) is a leader in trusted enterprise conversational AI and digital transformation. The world's leading brands use our award-winning Conversational Cloud platform to connect with millions of consumers. We power nearly a billion conversational interactions every month, providing uniquely rich data analytics and safety tools to unlock the power of conversational AI for better business outcomes. Fast Company named LivePerson the #1 Most Innovative AI Company in the world.

Job Description: Senior MySQL Database Engineer - 8+ Years Experience.

Please apply only if you have 8 plus years of experience. Profiles with less than 8 years of experience will be rejected.

Position Overview:

We are seeking a Senior MySQL Database Engineer (L3) with 8+ years of experience managing large-scale production database environments. This role combines deep technical expertise with strategic thinking, focusing on production reliability, platform engineering, automation, and architectural evolution.

The ideal candidate will be a technical leader who can design scalable database solutions, mentor team members, drive automation initiatives, and own complex production systems. You will work with CloudSQL on GCP, lead migration projects, implement SRE best practices, and collaborate across engineering teams to ensure database reliability at scale.

This role includes participation in 24/7 on-call rotations to ensure continuous support for our critical MySQL infrastructure.

Responsibilities:

Production Reliability & Platform Engineering

• Own and architect high-availability MySQL database platforms supporting critical business systems.
• Design and implement multi-region replication strategies, disaster recovery architectures, and zero-downtime migration patterns.
• Lead incident response for critical database outages, coordinate cross-functional teams, and drive post-incident reviews.
• Define and track database SLIs/SLOs, establish reliability metrics, and implement continuous improvement programs.
• Drive capacity planning at scale, forecast growth patterns, and architect for horizontal and vertical scaling.
• Establish database standards, operational runbooks, and best practices across the organization.

Automation & Infrastructure as Code

• Lead automation initiatives to eliminate toil and improve operational efficiency.
• Design and implement database provisioning platforms using Terraform and configuration management tools.
• Build self-service workflows for database creation, schema migrations, and routine operations.
• Architect and implement GitOps-driven database deployments integrated with CI/CD pipelines.
• Develop custom tooling and automation frameworks for database operations (Python, Go, or Bash).
• Drive adoption of infrastructure as code practices across database teams.

Cloud & Hybrid Architecture

• Lead CloudSQL (GCP) operations at scale, including advanced configurations, HA setups, and cross-region deployments.
• Design and execute cloud migration strategies from on-premises to GCP (or hybrid architectures).
• Implement multi-cloud or hybrid-cloud database strategies where applicable.
• Optimize cloud costs through right-sizing, reserved instances, and architectural improvements.
• Work with GCP native services (Cloud Monitoring, Secret Manager, VPC, IAM) for secure and scalable deployments.

Performance Engineering & Optimization

• Lead performance engineering initiatives including query optimization, indexing strategies, and schema design reviews.
• Conduct advanced troubleshooting of complex performance issues across application and database layers.
• Perform deep-dive analysis using tools like pt-query-digest, Percona Toolkit, and performance_schema.
• Design database sharding and partitioning strategies for scalability.
• Review and optimize backup/restore strategies for RTO/RPO requirements.

Observability & Reliability Engineering

• Design and implement comprehensive monitoring and alerting frameworks (Prometheus, Grafana, Cloud Monitoring).
• Build custom dashboards and SLO tracking for database reliability metrics.
• Implement proactive monitoring to detect issues before they impact production.
• Establish observability standards including logging, tracing, and metrics collection.

Technical Leadership & Mentorship

• Mentor L1/L2 database engineers on technical skills, troubleshooting methodologies, and best practices.
• Conduct code reviews, design reviews, and knowledge-sharing sessions.
• Drive technical decision-making for database architecture and tooling choices.
• Collaborate with application teams, SRE teams, and platform engineers on cross-functional projects.
• Represent database engineering in architectural discussions and technical forums.

Distributed Systems & Data Infrastructure (Good to Have)

• Work with Elasticsearch for search and analytics workloads.
• Support Kafka-based data pipelines and event-driven architectures.
• Integrate databases with Kubernetes-based application platforms.
• Collaborate on data platform initiatives involving data lakes, streaming, and analytics.

Required Qualification:

• 8+ years of hands-on MySQL DBA/Engineering experience in production environments.
• Expert-level knowledge of MySQL architecture, replication (async, semi-sync, GTID), performance tuning, and troubleshooting.
• 4+ years managing Cloud SQL on GCP, including HA configurations, read replicas, and backup strategies.
• 4+ years of Infrastructure as Code experience (Terraform strongly preferred), including module development and state management.
• 4+ years with configuration management tools (Ansible, Chef, or Puppet) in production environments.
• Proven experience building and maintaining CI/CD pipelines for database changes and schema migrations.
• Strong programming/scripting skills (Python, Bash, or Go) for automation and tooling development.
• Deep Linux system administration skills and understanding of OS-level performance tuning.
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK, or similar).
• Demonstrated leadership in incident response, including on-call rotations and post-mortem facilitation.
• Experience supporting large-scale production systems with strict uptime requirements (99.9%+).

Preferred Qualifications:

• Production experience with Elasticsearch (cluster management, indexing strategies, performance tuning).
• Hands-on experience with Kafka (topics, partitions, consumer groups, integration patterns).
• Led or participated in large-scale cloud migration projects (on-prem to cloud or cloud-to-cloud).
• Experience with Kubernetes and containerized database workloads (StatefulSets, operators).
• Familiarity with PostgreSQL or other RDBMS platforms.
• Experience with database security (encryption, IAM, audit logging, compliance).
• Knowledge of distributed databases or NoSQL systems (Cassandra, MongoDB, etc.).
• Exposure to data engineering tools (Airflow, dbt, Spark) and modern data architectures.
• Certifications: GCP Professional Database Engineer, MySQL Certification, or equivalent.

Benefits:

• Personal time off 15 days - Casual (6) days & Sick Days (6)
• Medical Insurance: 8 Lakhs Family Floater that covers employee, spouse, 3 children and parents or In-laws
• Group Personal Accident: 3x of the employee’s Gross Salary
• Group Term Life: 3x of the employee’s Gross Salary
• Volunteering Days – Use them to make a difference in your community. Whether it's a cleanup, supporting a local initiative or holding an “Ehrenamt”, just let us know! We're here to help you create a meaningful impact.

Financial & Growth

• Employee Stock Program (ESPP): Participate in our Employee Stock Participation Program and receive a discount on company shares, allowing you to share in LivePerson's success.
• Learning & Development: We actively support your professional journey with robust programs for growth and learning development, including allocated stipends, ensuring you reach your full potential.

Why You’ll Love Working Here

As leaders in enterprise customer conversations, we celebrate diversity, empowering our team to forge impactful conversations globally. LivePerson is a place where uniqueness is embraced, growth is constant, and everyone is empowered to create their own success. We're very proud to have earned recognition from Fast Company, Newsweek, and BuiltIn for being a top innovative, beloved, and remote-friendly workplace, and recognized by Gartner as a leader in the Conversational AI space.

Belonging at LivePerson

We are committed to fostering an inclusive workplace and are proud to be an Equal Opportunity Employer. We believe that diverse perspectives drive innovation. 

Accessibility Commitment

LivePerson is dedicated to the accessibility needs of our applicants and employees. We provide reasonable adjustments to job applicants with disabilities. Applicants who require a reasonable adjustment for any part of the application or hiring process should inform their recruiting contact upon initial connection.

Important Candidate Notice

The talent acquisition team at LivePerson has recently been notified of a phishing scam targeting candidates applying for our open roles. Scammers have been posing as hiring managers and recruiters in an effort to access candidates' personal and financial information. This phishing scam is not isolated to only LivePerson and has been documented in news articles and media outlets.

Please note that any communication from our hiring teams at LivePerson regarding a job opportunity will only be made by a LivePerson  employee with an @liveperson.com email address.

LivePerson does not ask for personal or financial information as part of our interview process, including but not limited to your social security number, online account passwords, credit card numbers, passport information and other related banking information. If you have any questions and or concerns, please feel free to contact recruiting-lp@liveperson.com

Senior Machine Learning Engineer

Location: (Bangalore or Noida) 

The proliferation of machine log data has the potential to give organizations unprecedented real-time visibility into their infrastructure and operations. With this opportunity comes tremendous technical challenges around ingesting, managing, and understanding high-volume streams of heterogeneous data

As a 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, 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.

Responsibilities

• Design, implement, and optimize agentic AI components, including context engineering, memory management, and prompts.
• 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.
• 4-6 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.
• Strong communication skills and a passion for shaping emerging AI paradigms.

Desired Qualifications

• 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. helps make the digital world secure, fast, and reliable by unifying critical security and operational data through its Intelligent Operations Platform. Built to address the increasing complexity of modern cybersecurity and cloud operations challenges, we empower digital teams to move from reaction to readiness—combining agentic AI-powered SIEM and log analytics into a single platform to detect, investigate, and resolve modern challenges. Customers around the world rely on Sumo Logic for trusted insights to protect against security threats, ensure reliability, and gain powerful insights into their digital environments. 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.

About the role

We are seeking an accomplished Data Engineer to join our dynamic and rapidly expanding Tech Ops division. With significant projected growth, this is an opportunity to drive meaningful technical impact. In this role, you will work directly with customers, data vendors, and internal engineering teams to design, implement, and optimize complex data integration solutions within a modern, large‑scale cloud environment.

You will leverage advanced skills in distributed computing, data architecture, and cloud-native engineering to enable scalable, resilient, and high‑performance data ingestion and transformation pipelines. As a trusted technical advisor, you will guide customers in adopting Abacus’s core data management platform and ensure high-quality, compliant data operations across the lifecycle.

Your day to day :

• Architect, design, and implement high-volume batch and real-time data pipelines using PySpark, SparkSQL, Databricks Workflows, and distributed processing frameworks.
• Build end‑to‑end ingestion frameworks integrating with Databricks, Snowflake, AWS services (S3, SQS, Lambda), and vendor data APIs, ensuring data quality, lineage, and schema evolution.
• Develop data modeling frameworks, including star/snowflake schemas and optimization techniques for analytical workloads on cloud data warehouses.
• Lead technical solution design for health plan clients, creating highly available, fault-tolerant architectures across multi-account AWS environments.
• Translate complex business requirements into detailed technical specifications, engineering artifacts, and reusable components.
• Implement security automation, including RBAC, encryption at rest/in transit, PHI handling, tokenization, auditing, and compliance with HIPAA and SOC 2 frameworks.
• Establish and enforce data engineering best practices, such as CI/CD for data pipelines, code versioning, automated testing, orchestration, logging, and observability patterns.
• Conduct performance profiling and optimize compute costs, cluster configurations, partitions, indexing, and caching strategies across Databricks and Snowflake environments.
• Produce high-quality technical documentation including runbooks, architecture diagrams, and operational standards.
• Mentor junior engineers through technical reviews, coaching, and training sessions for both internal teams and clients.

What you bring to the team :

• Bachelor’s degree in Computer Science, Computer Engineering, or a closely related technical field.
• 5+ years of hands‑on experience as a Data Engineer working with large‑scale, distributed data processing systems in modern cloud environments.
• Working knowledge of U.S. healthcare data domains—including claims, eligibility, and provider datasets—and experience applying this knowledge to complex ingestion and transformation workflows.
• Strong ability to communicate complex technical concepts clearly across both technical and non‑technical stakeholders.
• Expert‑level proficiency in Python, SQL, and PySpark, including developing distributed data transformations and performance‑optimized queries.
• Demonstrated experience designing, building, and operating production‑grade ETL/ELT pipelines using Databricks, Airflow, or similar orchestration and workflow automation tools.
• Proven experience architecting or operating large‑scale data platforms using dbt, Kafka, Delta Lake, and event‑driven/streaming architectures, within a cloud‑native data services or platform engineering environment—requiring specialized knowledge of distributed systems, scalable data pipelines, and cloud‑scale data processing.
• Experience working with structured and semi‑structured data formats such as Parquet, ORC, JSON, and Avro, including schema evolution and optimization techniques.
• Strong working knowledge of AWS data ecosystem components—including S3, SQS, Lambda, Glue, IAM—or equivalent cloud technologies supporting high‑volume data engineering workloads.
• Proficiency with Terraform, infrastructure‑as‑code methodologies, and modern CI/CD pipelines (e.g., GitLab) supporting automated deployment and versioning of data systems.
• Deep expertise in SQL and compute optimization strategies, including Z‑Ordering, clustering, partitioning, pruning, and caching for large‑scale analytical and operational workloads.
• Hands‑on experience with major cloud data warehouse platforms such as Snowflake (preferred), BigQuery, or Redshift, including performance tuning and data modeling for analytical environments.

What we would like to see but not required:

• Experience in large-scale healthcare or payer data environments.

What you’ll get in return :

• Competitive Leave & Benefits
• Comprehensive health coverage
• Equity for every employee – share in our success
• Growth-focused environment – your development matters here

Work arrangements :

• Standard hours: 8 hours/day, 5 days/week
• Location: Pune, Hybrid (3 days a week in office)
• Shift: 12pm-9pm IST

About Bold Business

Bold Business is an AI-first U.S.-based company building automation systems, AI agents, and production software for clients like AT&T, JP Morgan, and Verizon. We ship real systems that deliver impact — not experiments.

The Role

We’re hiring a Senior Python Engineer who can own both backend systems and the data layer behind them. This role sits between backend and data — you will build APIs, design pipelines, and ensure the data powering AI systems is clean and reliable.

You’ll work under a Lead Architect. You are expected to execute independently and own outcomes.

What You’ll Do

• Build and maintain production Python APIs (FastAPI or similar)
• Design and run data pipelines (ETL, ingestion, transformation)
• Own data quality — validation, monitoring, failure handling
• Structure data for RAG systems and AI agents
• Design and manage databases (PostgreSQL + vector DBs)
• Integrate external systems (APIs, webhooks, third-party tools)
• Debug across backend, data pipelines, and AI outputs

Non-Negotiables (Knockout Requirements)

You should not apply if you cannot clearly demonstrate all of the following:

1. Strong English communication (written and spoken)
   You can clearly explain technical concepts to non-technical stakeholders and operate in a U.S.-based team environment.
2. You have built and maintained production Python APIs
   (not tutorials or small scripts — real systems in use)
3. You have owned data pipelines end-to-end
   (ingestion → transformation → reliability in production)
4. You are strong in SQL and database design
   (schemas, performance, tradeoffs — not just basic queries)
5. You have worked with real, messy data
   (multiple sources, failures, edge cases — not clean datasets)

Required Skills

• Python (4–6 years, production backend + data work)
• FastAPI or similar frameworks
• Strong SQL and database design
• API integrations (REST, webhooks)
• Testing and clean Git workflows

AI / Data Context (Expected Working Level)

• LLM API integration (OpenAI, Anthropic, etc.)
• Understanding of how RAG systems use data
• Prompt structure and output handling
• Exposure to vector databases (pgvector, Pinecone, etc.)

Nice to Have

• LangChain, LangGraph, CrewAI
• Airflow, Prefect, or pipeline orchestration
• AWS / GCP experience
• Docker / CI-CD
• Basic BI / analytics tools

What This Role Is

• A hands-on builder role
• Ownership of backend + data layer
• High accountability, low hand-holding

What This Role Is Not

• Not a pure Data Engineer
• Not an ML research role
• Not a junior position

Final Note

• We will go deep into your past work.
• If you can clearly explain what you built, why you built it that way, and what broke — you’ll do well here.
• If not, this role will be a stretch.

Bold Business — AI-First. Delivery-First.

The Opportunity at Komodo Health

Komodo aims to build the best healthcare data architecture in the industry. We are rapidly growing and expanding our infrastructure stack and adopting SRE best practices. You will be joining the Platform team. We build, operate, and constantly improve our infrastructure offerings for 150+ client organizations. The team achieves our business goals by adopting best infrastructure practices and leveraging 100% automation to scale our product offerings and reduce costs. You will work with passionate team members across the country, and to accomplish our goal: reduce the burden of disease.

Looking back on your first 12 months at Komodo Health, you will have…

• Have developed a deep understanding of Platform and Platform customers 
• Have built and operated cloud infrastructure (AWS) based on customer requirements 
• Have solved any development and deployment challenges around making Platform infrastructure highly reliable, easy to maintain, and cost effective
• Have participated in the development, execution, and support of the new feature rollout with solution architects, forward-deployed engineers, and customer success teams
• Have developed and contributed to existing and new monitoring and alerting systems for Platform infrastructure
• Have hardened infrastructure security including network, storage, user access, etc. 
• Have responded and solved key customer reported issues in a timely manner
• Participated in an on-call rotation
• Spearheaded the adoption of AI-driven development workflows, integrating LLM-based tools into the SDLC to accelerate feature delivery and reduce mean time to resolution (MTTR).
• Architected and deployed custom MCP (Model Context Protocol) tooling and autonomous agents, enabling seamless data interoperability between internal systems and AI models to automate complex platform engineering tasks

What you bring to Komodo Health:

• Engineering Excellence: Proficiency in Python or Rust, with deep technical troubleshooting skills and extensive experience building backend APIs and microservices.
• Cloud Infrastructure: Expert-level knowledge of AWS core services and the ability to architect scalable solutions from high-level requirements.
• Kubernetes & Orchestration: Hands-on experience managing the "care and feeding" of Kubernetes clusters (upgrades, Service Mesh/Istio, Helm) and scaling compute services using ArgoCD and Argo Rollouts.
• Infrastructure as Code & CI/CD: Proficiency in Terraform/Scalr and experience building robust CI/CD pipelines using GitHub Actions or Jenkins.
• Networking & Connectivity: Solid understanding of networking fundamentals (subnets, CIDR, VPCs) to ensure secure, global application accessibility.
• Data Frameworks: Familiarity with big-data tools and workflow orchestrators such as Snowflake, Airflow, and Spark.
• AI & Productivity: Ability to leverage AI tools (Gemini, ChatGPT, Cursor) to streamline engineering workflows and enhance personal productivity.

Additional skills and experience we’d prioritize (nice to have)…

• Experience with AWS preferred. AWS Cloud Infrastructure certification is a plus. 
• Experience with data privacy concerns such as HIPAA or GDPR
• Working knowledge of data modeling and storage across relational (PostgreSQL), NoSQL (DynamoDB, Redis), and MPP databases (Snowflake, Redshift).
• Experience working with cross-functional teams and with other customer-facing teams
• Passion! We hope you are passionate about our mission and technology
• Ownership! We hope you own your work, be accountable, and push it through the finish line. We hope you treat yourself as a cofounder and do not hesitate to share any idea that helps Komodo
• Expertise! We do not need you to know everything, but we hope you have deep knowledge in at least one area and can start contributing quickly. And we would love to learn from you in your area(s) of expertise as well.

Job Title: Senior Full Stack Machine Learning Engineer

About Us:

Inovalon is a leading healthcare technology company dedicated to revolutionizing the healthcare industry through innovative AI and machine learning solutions. Our mission is to leverage cutting-edge technology to improve health outcomes and streamline healthcare processes. We are looking for a talented and experienced Senior Full Stack Machine Learning Engineer to join our dynamic team.

Job Description:

• As a Senior Full Stack Machine Learning Engineer, you will play a pivotal role in designing, developing, and deploying machine learning models that drive our healthcare solutions. You will work closely with data scientists, software engineers, and product managers to build scalable and robust machine learning systems. Your expertise will help us transform healthcare data into actionable insights, ultimately improving patient care and operational efficiency.

Key Responsibilities:

• Model Development: Design, implement, and optimize machine learning models for various healthcare applications, including predictive analytics, natural language processing, and generative AI.
• End-to-End Deployment: Develop and maintain the full lifecycle of machine learning solutions, from data preprocessing and model training to deployment and monitoring in production environments.
• Data Engineering: Collaborate with data engineers to build and maintain data pipelines, ensuring the availability of high-quality data for training and inference.
• Software Development: Write clean, efficient, and maintainable code for machine learning applications, ensuring seamless integration with existing systems.
• Performance Optimization: Continuously monitor and improve the performance of machine learning models and systems, addressing issues related to scalability, latency, and accuracy.
• Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions.
• Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of continuous learning and innovation.

Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
• Experience: Minimum of 5 years of experience in machine learning, with a proven track record of deploying models in production environments.

Technical Skills:

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in building applications leveraging generative AI technologies which includes LLM’s, prompt engineering, Vector Databases, RAG architectures and transfer learning is a plus.
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Strong knowledge of data structures, algorithms, and software engineering best practices.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and data pipeline tools (e.g., Airflow, Kafka).
• Experience with frontend and backend development, including frameworks such as React, Node.js, and Django.

Domain Knowledge: Understanding of healthcare data standards (e.g., HL7, FHIR) and regulations (e.g., HIPAA) is a plus.

Soft Skills:

• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work independently and as part of a team in a fast-paced environment.

What We Offer:

• Competitive salary and benefits package.
• Opportunity to work on impactful projects that improve healthcare outcomes.
• Collaborative and innovative work environment.
• Professional development and growth opportunities.
• Flexible work arrangements, including hybrid and remote options.

Join us in our mission to transform healthcare through technology! We look forward to hearing from you.

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 Big Data Infrastructure operates the critical infrastructure that powers the batch data processing at Stripe. The team supports a variety of use cases, including Payment, Ledger, ML, Fraud Detection, Product Analytics, Regulatory Reporting, Financial Data Reconciliation, and externally facing products like Radar and Sigma. As an example of the scale, the team’s systems serve hundreds of teams, thousands of workflows, 100,000+ task executions, O(billion) transformations, and moving terabytes of data processing over 1 GB/second every day. Our users inside Stripe include other engineering teams, Data Scientists, Sales & Operations, Finance, etc. 

Data Orchestration builds and operates the time-based and event-based orchestration infrastructure that powers and accelerates batch data pipelines. The team operates on a wide range of tech stacks including Airflow, Spark, SQL, Kafka, Flink, Hive MetaStore, Trino, Pinot, Python, Java, Scala, S3, and Iceberg. 

What you’ll do 

As a Software Engineer on our team, you will do the following: 

• Design, build, and maintain innovative next-generation or first-generation versions of key Data Platform products, with an emphasis on usability, reliability, security, and efficiency. 
• Design ergonomic APIs and abstractions that build a great customer experience for internal Stripes, that will in turn enhance the experience of millions of Stripe users.
• Ensure operational excellence and enable a highly available & reliable Data Orchestration platform across batch workloads. 
• Collaborate nimbly with high-visibility teams and their stakeholders to support their key initiatives - while building a robust platform that benefits all of Stripe in the long term. 
• Plan for the growth of Stripe’s infrastructure by unblocking, supporting, and communicating proactively with internal partners to achieve results. ● Connect your work with improvements in the usability and reliability of Open Source Software (OSS) like Apache Airflow, Iceberg, Spark and contribute back to the OSS community. 

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 

• 8+ years of professional experience writing high quality production level code or software programs and interest in Data Infrastructure. 
• Has experience operating or enabling large-scale, high-availability data pipelines from design, to execution and safe change management. Expertise in Spark, Flink, Spark, Airflow, Python, Java, SQL, and API design is a plus. 
• Has experience developing, maintaining, and debugging distributed systems built with open source tools 
• Has experience building infrastructure-as-a-product with a strong focus on users needs 
• Has strong collaboration and communication skills, and can comfortably interact with both technical and non-technical participants. 
• Has the curiosity to continuously learn about new technologies and business processes. 
• Is energized by delivering effective, user-first solutions through creative problem-solving and collaboration. 

Preferred qualifications 

• Has experience writing production-level code in Expertise in Scala, Spark, Flink, Spark, Airflow, Python, Java, and SQL is a plus.
• Has experience designing APIs or building developer platforms ● Has experience optimizing the end to end performance of distributed systems ● Has experience with scaling distributed systems in a rapidly moving environment ● Has experience working with Airflow Infrastructure. 
• Genuine enjoyment of innovation and a deep interest in understanding how things work 

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams. 

Office location - Bengaluru , KA, India 

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.

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.

What You’ll Do:

In this role, you will take the lead in designing, building, and optimizing data pipelines, ensuring high-quality data integration and real-time analytics. As a Senior Staff Engineer, you will mentor and guide a team of data engineers, collaborate with cross-functional teams, and drive best practices for data architecture and engineering.

• Leadership & Mentorship:
  • Lead and mentor a team of engineers, ensuring technical excellence and continuous improvement.
  • Provide guidance on complex technical issues, and foster a culture of collaboration and innovation.
  • Develop and maintain data engineering processes, practices, and standards across the team.
• Data Architecture & Engineering:
  • Design and develop robust, scalable, and efficient data pipelines for ETL (Extract, Transform, Load) processes.
  • Architect data solutions and ensure seamless integration of data from diverse sources, both on-premise and in the cloud.
  • Optimize data storage, retrieval, and processing for performance and scalability.
• Collaboration & Stakeholder Management:
  • Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions that meet business needs.
  • Collaborate with the software engineering team to ensure smooth integration of data pipelines into applications.
• Data Quality & Governance:
  • Ensure data integrity, quality, and consistency across systems.
  • Implement and enforce data governance policies and best practices, ensuring compliance with data privacy regulations.
• Continuous Improvement:
  • Stay updated with the latest trends in data engineering, big data technologies, and cloud platforms.
  • Drive automation, testing, and optimisation within data pipelines to improve overall efficiency.
• Technology Stack:
  • Lead the selection and implementation of appropriate technologies for data storage, processing, and retrieval (e.g., Hadoop, Spark, Kafka, Airflow).
  • Experience working with public clouds like GCP/AWS.
  • Proficient with SQL, Java, Spring boot, Python or at least one Object oriented language, Bash.
  • Experience with any of Apache open source projects such as Spark, Druid, Beam, Airflow etc. and big data databases like BigQuery, Clickhouse, etc.

Who You Are:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent work experience).
• 8+ years of experience in data engineering or related roles, with at least 2 years in a leadership or senior technical position.
• Extensive experience with data warehousing, ETL pipelines, data modeling, and data architecture.
• Strong experience working with large-scale data processing frameworks (e.g., Hadoop, Apache Spark, Kafka).
• Proficient in SQL, Python, Java, or other relevant programming languages.
• Hands-on experience with cloud-based platforms (AWS, GCP, Azure).
• Familiarity with data orchestration tools like Apache Airflow or similar.
• Strong knowledge of databases (SQL and NoSQL) and data storage technologies.
• Excellent problem-solving and analytical skills.
• Strong communication and interpersonal skills, with the ability to work effectively with both technical and non-technical teams.

Software Development Engineer III - Java Backend Engineer

India (Remote/Hyderabad)

Work Timings 2 PM to 11 PM IST 

LivePerson (NASDAQ: LPSN) is a leading customer engagement company, creating digital experiences powered by Curiously Human AI. Every person is unique, and our technology makes it possible for companies, including leading brands like HSBC, Orange, and GM Financial, to treat their audiences that way at scale. Nearly a billion conversational interactions are powered by our Conversational Cloud each month.

You'll be successful at LivePerson if you are excited to build something from the ground up. You excel by finding daily opportunities to grow at the same pace as the technology we're building, and you build partnerships that improve our business. Likewise, you're someone who sees feedback as a chance to learn and grow and believe decisions powered by data are the norm. You care about the well-being of others and yourself.

Job Description: Senior Software Engineer (Java, Python, Cloud Native, Generative AI) - 8+ Years Experience from a Product Based IT Company

Overview:

We are looking for a highly motivated and experienced Senior Java Engineer to join our engineering team. In this high-impact role, you will own the design and implementation of significant portions of our product development, specifically working with our Bots & Automation team to build a next-generation bot runtime platform.

You will serve as a technical leader and mentor for a small team of engineers, driving best practices in distributed systems and software architecture. If you have a passion for building reliable, scalable, and high-performance services and possess exceptional technical expertise, we want to hear from you.

Responsibilities:

• Technical Leadership & System Design: Own the design and implementation of critical backend components. You will build high-volume, low-latency applications for mission-critical systems, ensuring high availability and performance.
• Next-Gen Platform Development: Collaborate closely with the Bots & Automation team to architect and build a next-generation bot runtime platform.
• Distributed Systems Engineering: Create reliable, scalable, and high-performance services. Your work will require a deep understanding of Computer Science fundamentals and practical experience building large-scale distributed systems.
• API Design: Design and develop secure, scalable REST-based backend services.
• Mentorship: Serve as a leader and mentor to other engineers, fostering a culture of technical excellence and continuous improvement.
• Operational Excellence: Debug production issues, maintain existing codebases, and ensure the stability of the platform. You will participate in on-call rotations to support mission-critical services.
• Documentation & Compliance: Develop technical specifications, architecture documentation, and ensure all software complies with strict security standards.

Qualification:

• Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).
• Solid understanding of Data Structures and Algorithm Design
• Strong programming skills in Java with good knowledge of multi-threading.
• Expert-level knowledge of Databases (SQL, NoSQL) like Cassandra, MySQL
• Experience with Data Processing frameworks like Kafka, Airflow, Apache Spark, Hadoop
• Experience building REST APIs and debugging distributed microservice-based applications
• Experience in Kubernetes
• Experience with Git, Jenkins, and other Development tools
• Experience with NodeJS & Python is a plus
• Cloud expertise in either Google Cloud Platform (GCP) or Amazon Web Services (AWS)

Benefits:

• Personal time off 15 days - Casual (6) days & Sick Days (6)
• Medical Insurance: 8 Lakhs Family Floater that covers employee, spouse, 3 children and parents or In-laws
• Group Personal Accident: 3x of the employee’s Gross Salary
• Group Term Life: 3x of the employee’s Gross Salary
• Volunteering Days – Use them to make a difference in your community. Whether it's a cleanup, supporting a local initiative or holding an “Ehrenamt”, just let us know! We're here to help you create a meaningful impact.

Financial & Growth

• Employee Stock Program (ESPP): Participate in our Employee Stock Participation Program and receive a discount on company shares, allowing you to share in LivePerson's success.
• Learning & Development: We actively support your professional journey with robust programs for growth and learning development, ensuring you reach your full potential.

Why You’ll Love Working Here

As leaders in enterprise customer conversations, we celebrate diversity, empowering our team to forge impactful conversations globally. LivePerson is a place where uniqueness is embraced, growth is constant, and everyone is empowered to create their own success. We're very proud to have earned recognition from Fast Company, Newsweek, and BuiltIn for being a top innovative, beloved, and remote-friendly workplace, and recognized by Gartner as a leader in the Conversational AI space.

Belonging at LivePerson

We are committed to fostering an inclusive workplace and are proud to be an Equal Opportunity Employer. We believe that diverse perspectives drive innovation. 

Accessibility Commitment

LivePerson is dedicated to the accessibility needs of our applicants and employees. We provide reasonable adjustments to job applicants with disabilities. Applicants who require a reasonable adjustment for any part of the application or hiring process should inform their recruiting contact upon initial connection.

Important Candidate Notice

The talent acquisition team at LivePerson has recently been notified of a phishing scam targeting candidates applying for our open roles. Scammers have been posing as hiring managers and recruiters in an effort to access candidates' personal and financial information. This phishing scam is not isolated to only LivePerson and has been documented in news articles and media outlets.

Please note that any communication from our hiring teams at LivePerson regarding a job opportunity will only be made by a LivePerson  employee with an @liveperson.com email address.

LivePerson does not ask for personal or financial information as part of our interview process, including but not limited to your social security number, online account passwords, credit card numbers, passport information and other related banking information. If you have any questions and or concerns, please feel free to contact recruiting-lp@liveperson.com

About the Job:

We're looking for an engineering manager for our Warehouse Scale team. In this role, you'll lead the team that builds and operates the foundational data infrastructure powering LaunchDarkly's warehouse-native products — data export pipelines, warehouse health checks, and warehouse connection setup.

You'll bring a balance of people management and technical leadership as you drive the development of critical platform infrastructure and foster a high-performing, collaborative engineering culture. You'll partner closely with Product Management and cross-functional teams to deliver reliable, scalable systems that enterprise customers depend on.

Responsibilities:

• Lead and develop a team of backend engineers, providing coaching, feedback, and career growth opportunities

• Partner with PM and Design to scope, estimate, and sequence roadmap items, making scope tradeoffs in real time

• Own the team's delivery of critical infrastructure — data export pipelines, DAG orchestration, warehouse health checks, and connection setup

• Collaborate with adjacent teams (Warehouse Integrations, Experimentation, Data Platform) on shared infrastructure decisions and cross-team dependencies

• Communicate roadmaps, risks, and progress clearly to engineering leadership and cross-functional stakeholders

• Build team working norms that promote collaboration, reduce silos, and keep engineers engaged

• Drive operational excellence — improve reliability, observability, and incident response for production data infrastructure

• Participate in hiring to grow the team and raise the engineering bar

Qualifications:

• 3+ years of experience in software engineering, with at least 2 years managing a team of backend or infrastructure engineers

• Experience building or operating data infrastructure at scale — pipelines, orchestration frameworks, or data platform systems

• Proven ability to partner with Product Management to translate business goals into engineering plans with reliable estimations

• Strong communication skills, especially in distributed team environments with cross-timezone collaboration

• Track record of coaching and developing engineers, including performance management, career growth planning, and technical mentorship

• Familiarity with observability practices (metrics, tracing, alerting, structured logging) and comfort with production incident response

• Experience with Go or comparable backend languages (Java, Python, Rust) is a plus

• Familiarity with data warehouse platforms (Snowflake, Redshift, BigQuery, Databricks) and data pipeline tooling (Airflow, Prequel) is a plus

About LaunchDarkly:

Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. 

The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by:

• Improving the velocity and stability of software releases, without the fear of end customer outages
• Delivering targeted experiences by easily personalizing features to customer cohorts
• Maximizing the business impact of every feature through the ability to experiment and optimize
• Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types
• Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability

At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status.

Do you need a disability accommodation?

Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. 

Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @LaunchDarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly  directly for confirmed job openings and links to apply.

Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com.

The salary range for this role is negotiable, the range being $6,000-$12,500 per month (Gross in USD), based on location and experience level.  

About Sezzle:

With a mission to financially empower the next generation, Sezzle is revolutionizing the shopping experience beyond payments, blending cutting-edge tech with seamless, interest-free installment plans that make shopping smarter and more accessible. We’re not just transforming payments; we’re redefining how people discover, interact with, and purchase the things they love while driving real impact on merchant sales through increased conversions and higher order values. As we continue to shape the future of fintech and retail, we’re building an innovative, dynamic team passionate about creating more than just a transaction but a truly unique shopping journey. If you’re excited about pushing boundaries in tech and delivering a game-changing experience for consumers and merchants alike, come join us at Sezzle and help create the future of shopping!

Compensation:

For this principal development role, with 12+ years of experience, the compensation range is  $6,000 - $12,500 USD based on location and experience level per month and in gross amount. This range acknowledges the extensive expertise, leadership capabilities, and significant contributions expected at this level, offering a competitive salary to reflect the value of advanced skills and experience

About the Role: 

We are seeking a talented and motivated, best-in-class Principal Engineer for our Data Infrastructure. This role presents an exciting opportunity to thrive in a dynamic, fast-paced environment within a rapidly growing team, with abundant prospects for career advancement.

Sezzle is growing; our data generation and consumption is growing with us at an increasing scale. Data is extremely valuable, and we want to empower the business, the engineers, and the rest of the organization to be able to read, write, and analyze large volumes of it quickly and efficiently.

Sezzle is a heavy consumer of MySQL, Postgres, and Redshift, leveraging AWS tooling with Aurora RDS and DMS. We use DBT-based transformations and similar toolkits to populate a rapidly growing data lake that supports multiple data warehouses. It’s scaled well with us so far, and we’re looking to continue improving it, but we also want to step into new tooling and technologies.

What you’ll do: 

• End to end ownership of our database and data warehousing infrastructure, its KPIs and its SLAs, including MySQL, Postgres, CDC capture, and Redshift.
• Lead optimizations in database and query performance.
• ​​Build and maintain tooling to help manage and upgrade our data infrastructure, continually improving with migrations and optimizations.
• Partner with Development to ensure we ship solid queries against a battle-tested schema to meet the needs of our products and business.

• Help Sezzle evolve our data systems beyond the current scale and stack with whatever tooling is necessary to handle processing high volumes of writes and events while performing complex ETL.
• Evaluate and integrate new technologies, guiding the evolution of Sezzle’s data infrastructure.
• Help data engineers and analysts optimize Redshift and warehouse performance, including query tuning, modeling improvements, and cost management.

What We look for: 

• 12+ years of experience in DBA, SRE, or Data Engineering roles, with a strong track record of scaling production-grade systems.
• Deep expertise with MySQL, Postgres, AWS Redshift or similar products, including performance tuning, table design, and workload management.
• Advanced proficiency in SQL.
• Strong hands-on experience with data replication and ETL/ELT frameworks, especially DBT, AWS DMS, or similar tools.
• Strong understanding of data modeling, distributed systems, and warehouse/lake design patterns.
• Ability to work in a fast-paced, collaborative environment with excellent communication and documentation skills.

Preferred Knowledge and Skills:

• Prior experience in high-growth, data-intensive fintech or similar regulated environments.
• Knowledge of lakehouse architectures and modern stacks such as Snowflake, Databricks, Iceberg, or Delta Lake.
• Some background in designing scalable, fault-tolerant data pipelines using modern orchestration tools (Airflow, Dagster, Prefect, etc.) processing anywhere from 100GB to 1 TB of new data a day
• Familiarity with streaming technologies (Kafka, Kinesis, Flink, Spark Streaming).
• High enthusiasm for using AI to be as productive as possible.

About You: 

• You have relentlessly high standards - many people may think your standards are unreasonably high. You are continually raising the bar and driving those around you to deliver great results. You make sure that defects do not get sent down the line and that problems are fixed so they stay fixed.
• You’re not bound by convention - your success—and much of the fun—lies in developing new ways to do things
• You need action - speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk-taking.
• You earn trust - you listen attentively, speak candidly, and treat others respectfully.
• You have backbone; disagree, then commit - you can respectfully challenge decisions when you disagree, even when doing so is uncomfortable or exhausting. You have conviction and are tenacious. You do not compromise for the sake of social cohesion. Once a decision is determined, you commit wholly.
• You deliver results - you focus on the key inputs and deliver them with the right quality and in a timely fashion. Despite setbacks, you rise to the occasion and never settle.

Sezzle’s Technology Stack:

• Languages: Golang, Typescript, Python
• Frontend: Typescript - React and React Native
• Backend: Golang
• Database: MySQL, Postgres, Elasticsearch
• DevOps & Cloud: AWS, Kubernetes
• Version Control: Git
• CI/CD: Gitlab
• Testing: Developer and AI-driven, focus on automated end-to-end, integration, and unit tests
• Open Source: Sezzle is focused on using open source, and we build what we can before buying!

What Makes Working at Sezzle Awesome? 

At Sezzle, we are more than just brilliant engineers, passionate data enthusiasts, out-of-the-box thinkers, and determined innovators; we are skilled musicians, yogis, cyclists, chefs, golfers, dog-lovers, and rock-climbers. We believe in surrounding ourselves with not only the best and the brightest individuals, but those that are unique and purpose-driven in all that they do. Our culture is not defined by a certain set of perks designed to give the illusion of the traditional startup culture, but rather, it is the visible example living in every employee that we hire.

#Li-remote #full-time

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.

Position Summary:

Bottomline is looking for a Data Engineer to grow with us.

The data engineer is responsible for designing, developing, and maintaining the infrastructure and systems required for data storage, processing, and analysis. They play a crucial role in building, managing and test (QA) the data pipelines that enable efficient and reliable data integration, transformation, and delivery for all data users across the enterprise. Bring innovation and add value to organisation by implementing AI driven solutions in different projects in Data Engineering area.

The Data Engineer will work on implementing data flows to make data available in the Enterprise Data Warehouse from systems of record and operational data stores.  The Data Engineer will get to work on best-in-class cloud technologies(Snowflake, Fivetran, AWS, Azure, Salesforce, Airflow etc) and AI projects for Data Engineering Projects.

Along with making data available in the Enterprise Data Warehouse the Data Engineer will work with Data Analysts to implement data models and calculate key business KPIs for the use of the wider business for reporting and analytics.

The Data Engineer will have the opportunity to learn and develop their skills by working on assignments as part of a Scrum Team. They should be delivery focused and driven to problem solve.

How you’ll contribute:

• Design and develop data pipelines that extract data from various sources, transform it into the desired format, and load it into the appropriate data storage systems. 

• Collaborate with data scientists and analysts to optimize models and algorithms for data quality, security, and governance. 

• Integrate data from different sources, including databases, data warehouses, APIs, and external systems. 

• Ensure data consistency and integrity during the integration process, performing data validation and cleaning as needed. 

• Transform raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques. 

• Optimize data pipelines and data processing workflows for performance, scalability, and efficiency. Come-up with solutions utilising AI concepts through co-pilot, GitHub to improve efficiency and scalability.
• Monitor and tunes data systems, identifies and resolves performance bottlenecks, and implements caching and indexing strategies to enhance query performance. 
• Implement data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data. Utilise AI through Co-pilot or GitHub or any other trending AI tools, to automate and seamlessly query data based on user inputs in plain English to assess accuracy, consistency and completeness
• Carry out Data QA to validate the pipelines and data post integration as a supporting hand for the QA team

• Take authority, responsibility, and accountability for exploiting the value of enterprise information assets and of the analytics used to render insights for decision making automated decisions and augmentation of human performance. 

• Collaborate with leaders to establish the vision for managing data as a business asset. 

• Establish the governance of data and algorithms used for analysis, analytical applications, and automated decision making. 

What will make you successful: 

• A bachelor’s degree in computer science, data science, software engineering, information systems, or related quantitative field
• At least four (4) years of work experience in data management disciplines, including data integration, optimization and data quality, or other areas directly relevant to data engineering responsibilities and tasks. 
• Proven project experience developing and maintaining data warehouses (Snowflake experience is preferable)
• Ability to design, build, and deploy data solutions that capture, explore, transform, and utilize data to support AI, ML, and BI 
• Strong ability in programming languages such as Java or Python and other scripting languages
• Previous experience with languages/tools such as SQL
• Significant experience working in the ETL process and building pipeline for data retrieval using Rest API’s. Knowledge in ETL tool like Talend, Informatica is preferable
• Proficiency in OLAP, Star, Dimensional, and Snowflake schemas.
• Basic knowledge of BI Tools – Power BI, Tableau.
• Basic knowledge of DevOps tools – GitHub, Atlassian Tools, VS Code etc
• Experience working in a structured development environment (i.e., environment with the standard SDLC process).
• Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure) and modern data warehouse tools (Snowflake, Databricks)
• Experience with database technologies such as SQL, NoSQL, Oracle, or Teradata
• Experience with using AI in Data Engineering/ Data Analysis work and experience in Data QA.
• Knowledge in Apache technologies such as Kafka, Airflow to build scalable and efficient data pipelines (nice to have).
• Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products.
• Expert problem-solving skills, including debugging skills, allowing the determination of sources of issues in unfamiliar code or systems, and the ability to recognize and solve repetitive problems.
• Excellent business acumen and interpersonal skills; able to work across business lines at a senior level to influence and effect change to achieve common goals.
• Ability to describe business use cases/outcomes, data sources and management concepts, and analytical approaches/options.

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