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

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

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.

What you'll do

Metropolis is seeking a Senior Analytics Engineer to join our Data Engineering and Analytics team. The ideal candidate will possess a passion for creating value using data and a strong foundation in all aspects of analytics engineering. In this pivotal role, you will be instrumental in making data accessible and actionable, facilitating informed decision-making throughout the company. You will partner and lead across multiple product team functions and domains and drive impact through your data vision and architecture.

What we're looking for

• 5+ years experience with data/analytics engineering
• 5+ years of experience with Python and SQL (preferably Snowflake)
• 3+ years of experience with dbt (dbt certification a plus)
• Owned large-scale data projects that drove significant impact across the company by effectively partnering with engineering, data analysts, data scientists, and other business stakeholders
• Mentored other stakeholders in Data Science/Analytics, PM, and Engineering on data best practices
• Led the design, implementation, and monitoring of large-scale data warehouses and data marts that enable clear product-focused insights
• An expert at SQL, window functions, STRUCT/ARRAY manipulation, and query optimization
• Promoted performance best practices for your tables depending on the database engine (partitions, sort keys, dist keys, clustering, incremental modeling)
• Designed systems with a test-driven approach in mind to trap bad quality data or highlight alerts as part of your data flow
• Familiarity with ELT (Extract, Load, Transform) processes and tools to prepare and clean data for analysis
• Skill in using tools like dbt to build data transformation pipelines

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

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

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

• Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
• You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
• Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

• Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
• Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
• Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
• Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
• Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
• Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
• Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
• Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

• 8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
• Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
• Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
• Background in computer vision, image processing, or visual transformer architectures
• Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
• Experience working with massive datasets (50TB+) and building scalable data pipelines
• Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
• Familiarity with RLHF-style preference tuning and model alignment techniques
• Experience with observability and monitoring stacks including metrics, logging, and tracing
• Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

Get to know Okta

Okta is The World’s Identity Company. We free everyone to safely use any technology—anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth.

At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box, we’re looking for lifelong learners and people who can make us better with their unique experiences. 

Join our team! We’re building a world where Identity belongs to you. 

The Data Enablement Team

Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers.  We make access to applications safe, secure, and seamless for the more than 100 million daily logins around the world. Our modern approach to identity enables this Tier 0 global service to deliver convenience, privacy, and security so customers can focus on innovation.

Within the Data organization, the Data Enablement team is chartered with creating scalable semantic models that make it safe for anyone to see and understand data. By partnering with product and engineering leaders, this team owns the data lifecycle from strategy to prototyping to implementation, executive dashboard and product level self-service support.

The Senior Data Analyst Opportunity

Reporting to the Manager, Data Enablement - this role will be responsible for unlocking analytics across the company. You will do this through a combination of data lifecycle ownership, data tooling enablement and outreach programs designed to foster the safe usage of scalable data models for reporting and analytic consumption.

You'll serve as a critical data and technical partner that empowers our Sales, TAM, and Customer Success teams with the deep product insights they need to succeed. An average week will find you partnering with these teams to understand their measurement needs, reviewing engineering plans to ensure we capture critical data signals from the Auth0 product and developing data products that drive key success metrics. You will have multiple tools and teams at your disposal to achieve the core outcome of creating product and customer insights that help our partners drive value and long-term customer success.

What you’ll be doing 

• Partner with peers and leaders in Sales, TAM, Customer Success, Product, Engineering and Program Management to develop scalable measurement strategies for our data assets, products and services
• Drive scalable, semantic data models that can support stakeholders both inside of Auth0 and across the enterprise
• Educate and enlighten data stakeholders with newly available objects and models that will unlock product, revenue, sales and business insights
• Build reusable data models that support key concepts of the business (Entitlement, Activation, Utilization, Engagement, etc.)
• Deliver executive dashboards and product insights based on foundational productionalized data models
• Partner with other analysts to create composite measures and insights that span Auth0 and the enterprise
• Ensure that data privacy and governance is a first priority at all stages of the data lifecycle

What you’ll bring to the role

• 5+ years of experience in analytics, data engineering, or analytics engineering, or product management
• 5+ years of hands-on experience with data visualization tools (Tableau, Looker, Streamlit, PowerBI, Sigma, Omni, etc.)
• 5+ years of SQL experience
• Strong understanding of data lifecycle management including instrumentation, governance, modeling and self-service interfaces
• Experience working within a Jira/Agile environment to manage and prioritize technical work.
• Build relationships with partners and stakeholders to understand product data needs, distill business requirements into technical documentation and prioritize work accordingly
• Excellent business acumen and emotional intelligence in ambiguous environments
• BA or higher, preferred; additional relevant work experience in lieu of a degree is acceptable

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

• Cloud based data warehouse technologies (Snowflake, BigQuery, Databricks, etc.)
• Data engineering (Python, dbt, Kafka, Parquet, DuckDB, etc.)
• Experience with version control systems (e.g., Git) and the Pull Request process.
• Proficiency with advanced data skills/code, such as working with Claude code or other LLM-based data analysis tools.
• Paywall, subscription or authentication based products

What you can look forward to as an Okta employee!

• Amazing Benefits
• Making Social Impact
• Fostering Diversity, Equity, Inclusion and Belonging at Okta 

Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.

#Hybrid_Bengaluru

#LI_Linkedin P24589_3405679

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

Sr Analyst, Field Analytics

As part of Okta’s Go-To-Market Strategy & Operations group, the Field Analytics team drives insight and scale within the global field organization. We serve as the core engine for the analytics and strategic analysis that enable our leaders to make data-driven decisions that determine the trajectory of Okta’s growth.

You will be responsible for building high-impact technical assets, ranging from executive Tableau dashboards to standardized Snowflake datasets, while staying at the forefront of AI-driven analytics workflows. You will partner with US-based leadership and local team members to ensure our reporting framework is scalable, accurate, and deeply aligned with Okta’s global GTM strategy.

Job Duties & Responsibilities:

• Analytics Delivery: Design, build, and maintain high-visibility Tableau dashboards and reporting assets that provide actionable insights to business partners across the global organization.
• Data Set Engineering: Build and optimize production-grade data sets in Snowflake, ensuring that all field data (Pipeline, Bookings, Productivity) is clean, structured, and easily accessible for self-service analysis.
• Documentation & Governance: Take ownership of the technical documentation for all GTM reporting assets, ensuring data lineage, metric definitions, and logic are clearly defined and accessible.
• AI Implementation: Champion the use of Generative AI tools to accelerate the analytics lifecycle, including automating SQL query generation, streamlining data preparation, and enhancing report documentation.
• Global Collaboration: Work cross-functionally with Field Operations, Business Systems, and Data & Insights teams to capture requirements and deliver technical solutions that support our go-to-market initiatives

Required Skills & Qualifications: 

• 5+ years of professional experience in Data Analytics or Business Intelligence, ideally within a global delivery model.
• Technical Stack Expertise in SQL (Snowflake), BI Visualization tool (Tableau), and CRM data (Salesforce)
• Practical experience using Generative AI (e.g., GPT, Gemini, or GitHub Copilot) to improve technical productivity.
• A strong "documentation-first" mindset with the ability to create clear, concise technical and functional manuals.
• A relentless curiosity and a desire to "build it and own it," working both independently and collaboratively across a global team.
• Proven ability to translate complex data logic into clear, concise narratives.

Preferred Qualifications: 

• Proficiency with scripting (python) & data modeling (dbt) 
• Deep understanding of enterprise software sales processes, field operations, and cross functional GTM mechanics.
• Proven ability to operate independently within a global model, taking complex requirements from US-based stakeholders, execute high-quality technical work during India business hours, and provide comprehensive handoffs that allow projects to progress 24/7 without real-time oversight.

#LI-Hybrid

#P24939

Get to know Okta

Okta is The World’s Identity Company. We free everyone to safely use any technology—anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth.

At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box, we’re looking for lifelong learners and people who can make us better with their unique experiences. 

Join our team! We’re building a world where Identity belongs to you. 

The Data Enablement Team

Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers.  We make access to applications safe, secure, and seamless for the more than 100 million daily logins around the world. Our modern approach to identity enables this Tier 0 global service to deliver convenience, privacy, and security so customers can focus on innovation.

Within the Data organization, the Data Enablement team is chartered with creating scalable semantic models that make it safe for anyone to see and understand data. By partnering with product and engineering leaders, this team owns the data lifecycle from strategy to prototyping to implementation, executive dashboard and product level self-service support.

The Senior Data Analyst Opportunity

Reporting to the Manager, Data Enablement - this role will be responsible for unlocking analytics across the company. You will do this through a combination of data lifecycle ownership, data tooling enablement and outreach programs designed to foster the safe usage of scalable data models for reporting and analytic consumption.

You'll serve as a critical data and technical partner that empowers our Sales, TAM, and Customer Success teams with the deep product insights they need to succeed. An average week will find you partnering with these teams to understand their measurement needs, reviewing engineering plans to ensure we capture critical data signals from the Auth0 product and developing data products that drive key success metrics. You will have multiple tools and teams at your disposal to achieve the core outcome of creating product and customer insights that help our partners drive value and long-term customer success.

What you’ll be doing 

• Partner with peers and leaders in Sales, TAM, Customer Success, Product, Engineering and Program Management to develop scalable measurement strategies for our data assets, products and services
• Drive scalable, semantic data models that can support stakeholders both inside of Auth0 and across the enterprise
• Educate and enlighten data stakeholders with newly available objects and models that will unlock product, revenue, sales and business insights
• Build reusable data models that support key concepts of the business (Entitlement, Activation, Utilization, Engagement, etc.)
• Deliver executive dashboards and product insights based on foundational productionalized data models
• Partner with other analysts to create composite measures and insights that span Auth0 and the enterprise
• Ensure that data privacy and governance is a first priority at all stages of the data lifecycle

What you’ll bring to the role

• 5+ years of experience in analytics, data engineering, or analytics engineering, or product management
• 5+ years of hands-on experience with data visualization tools (Tableau, Looker, Streamlit, PowerBI, Sigma, Omni, etc.)
• 5+ years of SQL experience
• Strong understanding of data lifecycle management including instrumentation, governance, modeling and self-service interfaces
• Experience working within a Jira/Agile environment to manage and prioritize technical work.
• Build relationships with partners and stakeholders to understand product data needs, distill business requirements into technical documentation and prioritize work accordingly
• Excellent business acumen and emotional intelligence in ambiguous environments
• BA or higher, preferred; additional relevant work experience in lieu of a degree is acceptable

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

• Cloud based data warehouse technologies (Snowflake, BigQuery, Databricks, etc.)
• Data engineering (Python, dbt, Kafka, Parquet, DuckDB, etc.)
• Experience with version control systems (e.g., Git) and the Pull Request process.
• Proficiency with advanced data skills/code, such as working with Claude code or other LLM-based data analysis tools.
• Paywall, subscription or authentication based products

What you can look forward to as an Okta employee!

• Amazing Benefits
• Making Social Impact
• Fostering Diversity, Equity, Inclusion and Belonging at Okta 

Okta cultivates a dynamic work environment, providing the best tools, technology and benefits to empower our employees to work productively in a setting that best and uniquely suits their needs. Each organization is unique in the degree of flexibility and mobility in which they work so that all employees are enabled to be their most creative and successful versions of themselves, regardless of where they live. Find your place at Okta today! https://www.okta.com/company/careers/.

Okta is an Equal Opportunity Employer/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to participate in the job application or interview process, please use this Form to request an accommodation.

Okta is committed to complying with applicable data privacy and security laws and regulations. For more information, please see our Privacy Policy at https://www.okta.com/privacy-policy/.

#Hybrid_Bengaluru

#LI_Linkedin P24588_3405678

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 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

POS-30314

HubSpot’s mission is to Help Millions of Organizations Grow Better. HubSpot’s Operations team is core to this goal by supporting the HubSpotters who attract, engage, and delight HubSpot’s customers. Our goal in Operations is to embed advanced analytics and algorithmic intelligence into the DNA of decision-making across Flywheel. Flexible, well-connected, well-architected data are the backbone of our strategy, along with the Analytics Engineers who create that landscape. 

We believe in the power of data to drive effective decision-making. We leverage data for both day-to-day operations (improving efficiency by surfacing the right data at the right time) and for strategy (fostering deep understanding of what makes our flywheel spin, and projecting how to spin it faster in the future). In this role, you’ll be a member of the Data, Systems, & Intelligence team to design and build a modern data foundation for efficient models and analyses. Your work will directly support analytic and ML products that will change the way we make decisions within Flywheel at HubSpot. 

We’re looking for Analytic Engineers with a strong interest in building and maintaining flexible, reusable architecture for our highest value data assets. In this role, you will develop a deep understanding of the business and analytics priorities to create solutions that will unlock our ability to scale and drive actionable insights.

In this role you’ll get to:

• Collaborate with both technical and non-technical areas of the business, bridging the gap between the business problem and the technical solution
• Build out scalable data models to analyze key parts of the HubSpot business
• Establish and uphold technical best practices in maintaining the data infrastructure and and contribute to the company's long term data strategy
• Support distributed operations teams as they utilize these foundational data models for reporting
• Perform complex root cause analysis of problems and subsequently, makes and implements recommendations to prevent future occurrences
• Expand our suite of dbt patterns and macros to enable flexible and easily extensible data structures
• Scope requirements with internal stakeholders and lead working groups to usher projects through their entire lifecycle while building clear roadmaps for cross-functional team members
• Learn from our team of Analytics engineers, as well as HubSpot’s greater AE community
• Mentor and upskill other analytics engineers to create an inclusive team environment while promoting diversity, inclusion and belonging

We are looking for people who have:

• Several years of hands-on SQL experience, relational databases, and data modeling
• Ability to document technical design documents and organizational skills
• Proven communication skills and ability to bridge between business leaders, engineers, and data scientists
• Experience distilling complex ideas and data for both executives and front-line reps
• Creative problem solving skills to identify flexible solutions to business questions
• Insatiable curiosity and interest in learning new things
• Snowflake, dbt, and/or Looker experience is a plus

Role

Confidence can sometimes hold us back from applying for a job. But we'll let you in on a secret: there's no such thing as a 'perfect' candidate. HubSpot is a place where everyone can grow. So however you identify and whatever background you bring with you, please apply if this is a role that would make you excited to come into work every day.

About HubSpot

HubSpot (NYSE: HUBS) is a leading customer relationship management (CRM) platform that provides software and support to help businesses grow better. We build marketing, sales, service, and website management products that start free and scale to meet our customers’ needs at any stage of growth. We’re also building a company culture that empowers people to do their best work through. If that sounds like something you’d like to be part of, we’d love to hear from you.

You can find out more about our company culture in the HubSpot Culture Code, which has more than 5M views, and learn about our commitment to creating a diverse and inclusive workplace, too. Thanks to the work of every employee globally, HubSpot was named the #1 Best Place to Work on Glassdoor in 2020, and has been recognised for award-winning culture by Great Place to Work, Comparably, Fortune, Entrepreneur, Inc., and more.

Headquartered in Cambridge, Massachusetts, HubSpot was founded in 2006. Today, thousands of employees work across the globe in HubSpot offices and remotely. Visit our careers website to learn more about culture and opportunities at HubSpot. 

By submitting your application, you agree that HubSpot may collect your personal data for recruiting, global organization planning, and related purposes.  Please see HubSpot's Recruiting Privacy Notice for more information. 

About the role:

As a Sr. Manager, Platform & Architecture you will lead the definition, governance & continuous evolution of the enterprise data architecture vision and roadmap, ensuring strong alignment with business strategy and digital transformation goals. This role is accountable for establishing modern, secure, and scalable data platform architectures that enable advanced analytics, AI/ML, generative AI, and self service data capabilities across the organization.

You will provide strategic leadership in embedding AI into the enterprise data platform, enabling use cases such as predictive analytics, intelligent automation, and generative AI, while ensuring responsible AI practices, model governance, data quality, and regulatory compliance.

The role requires deep expertise in data architecture, cloud data platforms, analytics ecosystems, and platform security, combined with strong people and stakeholder management skills. You will guide the evaluation and adoption of emerging technologies, oversee PoC initiatives, and drive the operationalization of AI/ML and GenAI solutions.

Working closely with data engineering, analytics, AI/ML, security, and business leaders, you will ensure the delivery of trusted, high performing, and future ready data and AI platforms that scale with organizational needs.

What you'll do:

Strategic Leadership & Architecture Vision

• Define and own the enterprise data architecture vision and roadmap aligned with business strategy.
• Establish architectural principles, standards, and best practices across data modeling, integration, metadata, and analytics
• Guide architectural decisions to support scalability, performance, security, and future growth.
• Evaluate and approve new data technologies, platforms, and tools

Team Management & Development

• Lead, mentor, and manage data modelers & architects, platform engineers and data engineers
• Set goals, conduct performance reviews, and support career growth and skills development
• Ensure effective workload planning, prioritization, and resource allocation
• Promote a culture of collaboration, documentation, and architectural discipline

Data Platform & Architecture Design

• Design and oversee end to end data architectures, including ingestion, storage, processing, analytics, and consumption layers
• Define scalable patterns for batch, near real time, and streaming data processing
• Establish standards for data platforms, ingestion frameworks, transformation and modeling approaches, and BI/visualization tools
• Ensure platform reliability, performance, scalability, and cost optimization

Platform Engineering, Security & Governance

• Architect platforms with security by design, including IAM, RBAC, data encryption, masking, and auditing
• Collaborate with security and compliance teams to meet regulatory and data privacy requirements
• Define and enforce data governance standards, including metadata management, lineage, data quality, and observability
• Support platform monitoring, availability, and operational excellence

Advanced Analytics & Innovation

• Enable advanced analytics use cases, including forecasting, predictive modeling, and statistical analysis
• Support data science and analytics teams by designing architectures for ML pipelines, feature stores, and model deployment
• Lead Proof of Concept (PoC) initiatives to evaluate new data, analytics, and platform tools
• Assess emerging technologies for scalability, security, integration, and business value

Self-Service & Data Enablement

• Drive the self-service analytics strategy to empower analysts and business users
• Design curated, governed data layers and semantic models for trusted self-service access
• Reduce dependency on IT by enabling reusable data assets and standardized analytics frameworks
• Partner with stakeholders to align data products with business needs

Experience you'll need:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or related field
• 10 - 15+ years of experience in data engineering, analytics, or platform architecture roles
• Strong experience designing and implementing modern data architectures and cloud data platforms.
• Hands-on and architectural experience with:
  • Snowflake or similar cloud data warehouse/data lake experience
  • Tableau or similar BI tools
  • Fivetran or equivalent ingestion tools
  • dbt or similar data transformation frameworks
• Proficiency in SQL, Python, Spark, and data modeling techniques.
• Experience with cloud platforms such as AWS, Azure, or GCP

Preferred Qualifications:

• Experience with advanced analytics, forecasting, and predictive modeling.
• Knowledge of ML/AI platforms and MLOps concepts.
• Strong understanding of data security, governance, and compliance frameworks.
• Excellent communication and stakeholder management skills.
• Experience working in large-scale or enterprise Data & Analytics environments.

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

• Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
• You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
• Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

• Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
• Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
• Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
• Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
• Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
• Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
• Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
• Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

• 8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
• Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
• Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
• Background in computer vision, image processing, or visual transformer architectures
• Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
• Experience working with massive datasets (50TB+) and building scalable data pipelines
• Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
• Familiarity with RLHF-style preference tuning and model alignment techniques
• Experience with observability and monitoring stacks including metrics, logging, and tracing
• Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

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.

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.

**This is a hybrid role, requiring 2 days per week in our Bangalore office**

Reporting directly to the Director of Engineering, the Lead Engineer will guide the design and implementation of the software solutions under the User Generated Content (UGC) business division. Our teams work across the front-end (React & Elm), backend (Java/Kotlin), Data (Snowflake, dbt, Tableau), DevOps, and QA. We need a seasoned engineer who can shape the long-term design of our system. This person will guide our teams in architecting product features in a way that moves us towards that vision. We have a team-oriented culture, value collaboration, self-direction, and continuous improvement. We learn from our experiences to always improve, and we have fun and celebrate our successes.

HOW WE’LL BE WINNING TOGETHER DAY TO DAY

• Establish and champion the high-level, long-term architectural strategy for the UGC division’s suite of products
• Ensure software architecture aligns with the established technical strategy by establishing an Architecture Review Committee
• Advocate regulatory compliance, security policies, and processes in adherence to Industry standards and 1World Sync guidelines
• Drive continuous upgrades and enhancements of the various frameworks and tools used by the applications and the team.
• Assess, identify, and mitigate common issues in the operations of the software suite preemptively
• Develop the engineering team's capability in architectural design and implementation through mentorship and enablement
• Lead the research, evaluation, and adoption of new technologies to advance and upgrade our solutions.
• Partner with product and business leadership to ensure the technical strategy effectively addresses customer requirements and business goals
• Drive enhancements in engineering-wide practices, including CI/CD, testing, monitoring, security, and developer experience tooling

WE SHOULD TALK IF THIS SOUNDS LIKE YOU 

• 10+ years of software development experience
• 7+ years of full-stack application development using Object oriented programming(Kotlin, Java) and modern frameworks
• 3+ years of experience designing and implementing solutions with AWS
• 3+ years of experience with event-driven development (SQS, SNS, Kafka, Kinesis, Pub/Sub) and idempotent patterns
• 5+ years of experience developing APIs for front-end applications
• 5+ years of experience with relational databases (PostgreSQL, MySQL) and large data sets
• 3+ years of experience leveraging and maintaining CI/CD tooling (CircleCI, GitHub Actions)
• 3+ years of experience leveraging infrastructure as code using Terraform
• Experience leveraging automated database DDL (Liquibase, Flyway) (preferred but not required)
• Experience with object data stores (AWS S3, Azure Blob Storage, GCP Cloud Storage) and/or document data stores (AWS DynamoDB, MongoDB, NoSQL) (preferred but not required)
• Experience building containerized applications (Docker) and deploying them to orchestration (AWS ECS, Kubernetes, Docker Swarm) (preferred but not required)
• Experience with Data engineering and Analytics (Snowflake, dbt, Tableau) (preferred but not required)
• AWS Solutions Architect Associate Certification (preferred but not required
• BS degree in Computer Science, a similar technical field, or equivalent practical experience

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

• Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
• You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
• Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

• Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
• Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
• Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
• Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
• Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
• Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
• Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
• Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

• 6+ years of software engineering experience with 4+ years focused on AI/ML systems in production
• Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
• Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
• Background in computer vision, image processing, or visual transformer architectures
• Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
• Experience working with massive datasets (50TB+) and building scalable data pipelines
• Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
• Familiarity with RLHF-style preference tuning and model alignment techniques
• Experience with observability and monitoring stacks including metrics, logging, and tracing
• Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

Reports To

Director, NOC Delivery & Automation

What You Will Be Doing

• Lead the development of cutting-edge AI solutions across Voice AI, Computer Vision, and Conversational AI domains.
• You will architect and build production-grade AI systems that enhance our monitoring and analytics platform, improve customer support experiences, and enable intelligent automation across our EV charging infrastructure.
• Work closely with cross-functional teams to design, build, and deploy AI-powered solutions that directly improve the experience for millions of EV drivers and operators worldwide.

What You Will Bring to ChargePoint

• Deep expertise in Python, FastAPI, Django, and modern backend frameworks for AI service development
• Hands-on experience with LLM engineering: LangChain, LangGraph, Amazon Bedrock/OpenAI APIs, prompt engineering, and RAG architectures
• Strong experience with Elasticsearch including vector search, hybrid search (BM25 + dense embeddings), and semantic retrieval
• Proficiency with vector databases (Qdrant, ChromaDB, Pinecone) and embedding-based retrieval systems
• Experience building production LLM systems with focus on low-latency inference, caching strategies, and observability
• Strong foundation in distributed systems design, microservices architecture, and event-driven patterns (Kafka, RabbitMQ)
• Experience with cloud platforms (AWS/GCP), containerization (Docker, Kubernetes), and CI/CD pipelines
• Strong knowledge of PostgreSQL (query optimization, schema design), Redis, MongoDB, and message queues
• Track record of optimizing system performance with measurable improvements (latency reduction, cost optimization)

Requirements

• 8+ years of software engineering experience with 4+ years focused on AI/ML systems in production
• Tech/B.E. or M.S. in Computer Science, Machine Learning, or related field from a top-tier institution
• Experience with Voice AI systems, telephony integrations (Genesys, SIP), and speech processing pipelines
• Background in computer vision, image processing, or visual transformer architectures
• Data engineering experience with Airflow, DBT, and analytics platforms (ClickHouse, Trino, Iceberg)
• Experience working with massive datasets (50TB+) and building scalable data pipelines
• Hands-on experience with model fine-tuning techniques (LoRA/QLoRA) for domain-specific applications
• Familiarity with RLHF-style preference tuning and model alignment techniques
• Experience with observability and monitoring stacks including metrics, logging, and tracing
• Certifications in Generative AI, Agentic AI, or related specialization.

Location

Bangalore, India

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.

Overview of Role

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

Key Responsibilities

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

Required Technical Skillset

Experience & Qualifications

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

ABOUT THE ROLE

You are a seasoned Data Scientist, passionate about building robust, real-time machine learning solutions to combat financial crime. Working within the Risk & Fraud Team, you will leverage advanced statistical modeling and machine learning to detect, prevent, and adapt to evolving fraud threats. You thrive on solving complex problems with highly imbalanced data and delivering tangible risk reduction impact in a fast-paced environment.

You strongly believe in agile principles and use them to deliver value incrementally. You are eager to learn about new methodologies and practices and apply them directly in your work.

As a Senior Data Scientist you’ll be:

• Model Development & Risk Mitigation: Design, develop, and implement advanced ML/Statistical models to predict and prevent various fraud typologies. Focus on driving impact by optimising costs and reducing risk using ML/Stats models.
• Specialised Data Handling: Employ advanced techniques to manage and model highly imbalanced, large datasets characteristic of the fraud domain.
• Adaptive Systems: Build and maintain models that can quickly adapt to new and evolving fraud typologies and emerging threats.
• Real-Time MLOps: Develop, optimise, and deploy ML models for real-time/low-latency inference in production settings.
• Data & Feature Engineering: Utilize, enrich, and contribute to the feature store ecosystem, ensuring high-quality, scalable features for risk models.
• Performance Monitoring: Implement and maintain robust drift monitoring and model performance tracking to ensure deployed models remain effective and stable.
• Collaboration: Work closely with ML Engineers to productionize models leveraging AWS/GCP tech stack, and collaborate with Business and Product teams to understand requirements and solutionise data products.
• Exploration: Identify creative solutions in order to build relevant training data sets and explore the value of new data structures like knowledge graphs for relational fraud detection.

WHAT ARE WE LOOKING FOR

• You have 6+ years of experience in Software Development or Machine Learning, with a strong emphasis on practical model development and deployment.
• You are Strong in Python and have expert knowledge with Machine Learning tools/libraries (e.g., scikit-learn, statmodels, TensorFlow, Keras, or PyTorch).
• You have experience with big-data technologies such as Spark, SparkML, Hadoop etc. and have handled large data in a distributed processing environment. AWS, GCP, or Azure (anyone) cloud knowledge is preferred.
• You are proficient in ML training, optimising, feature selection and engineering, hyperparameter tuning and have knowledge about trade-offs in using different algorithms.
• You have demonstrated experience in developing and deploying a variety of ML-algorithms (e.g., logistic regressions, boosted trees, neural networks) that work in real-time settings.
• You have a good working knowledge with basic data table operations (SQL etc.), and data transform in the warehouse (dbt etc.).
• You are comfortable with ambiguity and are a self-starter—you take initiative in spotting opportunities and finding ways to solve challenges with data.
• Familiarity with Financial Services and Fintech space is preferred.
• You will be helping optimise all aspects of our sales funnel including finding ways to increase lead quality, reduce our cost of acquisition, optimise lead allocation, and improve the likelihood of successful lending outcomes for our members

Highly Desirable Skills:

• Exposure to Cost-Sensitive Learning techniques, where the economic impact of prediction errors is a key optimization factor.
• A decent idea and practical exposure to MLOps principles (e.g., model versioning, continuous integration/deployment for ML).
• Experience with Drift monitoring tools and frameworks.
• Exposure to Knowledge Graphs or graph database applications.

• Competitive Compensation -  competitive salary and share options
• Time Off – Generous annual leave on top of bank holidays.
• Parental Leave – Paid maternity, paternity, and adoption leave to support your family journey.
• Sabbatical – Extended unpaid and paid leave options after completing milestone years with Tide.
• Health Insurance – Private family insurance with additional OPD coverage and top-up options.
• Life & Accident Cover – Comprehensive accidental and life insurance protection.
• Mental Wellbeing – Access to therapy sessions, courses, meditations, and workshops.
• Volunteering & Development Days – Paid days annually for volunteering or personal growth.
• Learning & Development – Annual budget for books, courses, coaching, and more.
• WOO (Work Outside the Office) – Work from abroad for up to 90 days annually.
• Home Office Setup – Contribution towards setting up your home office
• Laptop Ownership – Keep your old laptop and get a new one when it’s time for a replacement.
• Snacks & Meals – Office perks with snacks, coffee, tea, and lunch (location dependent).

TIDEAN WAYS OF WORKING

At Tide, we champion a flexible workplace model that supports both in-person and remote work to cater to the specific needs of our different teams. 

While remote work is supported, we believe in the power of face-to-face interactions to foster team spirit and collaboration. Our offices are designed as hubs for innovation and team-building, where we encourage regular in-person gatherings to foster a strong sense of community.

About the role

We’re looking for a Staff Data Engineer to help design and build our next-generation data platform from the ground up. This is a high-impact, hands-on role where you’ll define core architectural decisions, set engineering standards, and partner closely with analytics, product, and engineering teams to unlock data at scale.

If you enjoy building platforms (not just using them), making long-term technical bets, and mentoring strong engineers, this role is for you.

Responsibilities

• Architect and build the foundational data platform that powers analytics, experimentation, and data products
• Establish best practices for data modeling, orchestration, testing, and observability
• Build and optimize data infrastructure on AWS (storage, compute, networking, security)
• Partner with stakeholders across Product, Analytics and Engineering to translate business needs into robust data solutions
• Drive technical decisions around performance, cost optimization, and data quality
• Mentor and guide other data engineers, raising the bar for technical excellence across the team
• Own critical systems end-to-end and participate in long-term platform roadmap planning
• Ensuring operational efficiency and actively participating in organizational initiatives with the objective of ensuring the highest customer value.

Must Have:

• 7+ years of experience in data engineering or platform engineering roles
• Strong hands-on experience with Spark, Python, and SQL in production environments
• Experience designing and operating large-scale data systems on cloud infrastructure (AWS preferred)
• Deep understanding of data modeling, distributed systems, and performance tuning
• Proven ability to lead technical initiatives and influence architecture across teams
• Comfortable working in ambiguous, early-stage environments where you help define the “right way”

Good To Have:

• Experience with Trino (or similar distributed SQL query engines)
• Experience using dbt for data transformations and modeling
• Familiarity with modern data stack concepts (lakehouse architectures, columnar storage, open table formats)
• Experience building internal data platforms or shared infrastructure
• Experience with Kubernetes, particularly Amazon EKS, for deploying and operating data workloads
• Proficiency in Apache Spark & Apache Kafka. 

About the Role

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

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

Key Skills

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

Key Responsibilities

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

P-1348

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

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

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

The impact you will have:

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

What we look for:

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

About the Customer Success Team:

Mixpanel’s Customer Success & Solutions Engineering teams are analytics consultants who embed themselves within our enterprise customer teams to drive our customers’ business outcomes. We work with prospects and customers throughout the customer journey to understand what drives value and serve as the technical counterpart to our Sales organization to deliver on that value. You will partner closely with Account Executives, Account Managers, Product, Engineering, and Support to successfully roll out self-serve analytics within our customers’ organizations, help the customer manage change, execute on technical projects and services that delight our customers, and ultimately drive ROI on the customer’s Mixpanel investment.

About the Role:

As a CSA, you will partner with customers throughout the customer journey to understand what drives value, beginning from the pre-sales running proof of concepts to demonstrate quick time to value, to post-sales onboarding and implementation, where you set customers up for long-term success with scalable implementation and data governance best practices. Throughout the entire customer lifecycle, you will work to understand how analytics can drive business value for your customers and will consult them on how to maximize the value of Mixpanel, including managing change during Mixpanel’s rollout, defining and achieving ROI, and identifying areas of improvement in their current usage of analytics. For large enterprise customers, post onboarding, you will also continue alongside the Account Managers to drive data trust and product adoption for 100+ end user teams through a change management rollout approach.

Responsibilities:

• Serve as a trusted technical advisor for prospects/customers to provide strategic consultation on data architecture, governance, instrumentation, and business outcomes
• Effectively communicate at most levels of the customer’s organization to influence business outcomes via Mixpanel, design and execute a comprehensive analytics strategy, and unblock technical and organizational roadblocks
• Own the customer’s success with Mixpanel — documenting and delivering ROI to the customer throughout their journey to transform their business with self-serve analytics
• Own onboarding and data health for your assigned customers/projects, including ongoing enhancements to their data quality and overall tech stack integration
• Engage with customers’ engineering, product management, and marketing teams to handle technical onboarding, optimize Mixpanel deployments, and improve data trust
• Deliver a variety of technical services ranging from data architecture consultations to adoption and change management best practices
• Leverage modern data architecture expertise to create scalable data governance practices and data trust for our customers, including data optimization and re-implementation projects
• Successfully execute on success outcomes whilst balancing project timelines, scope creep, and unanticipated issues
• Bridge the technical-business gap with your customers — working with business stakeholders to define a strategic vision for Mixpanel and then working with the right business and technical contacts to execute that vision
• Collaborate with our technical and solutions partners as needed on data optimization and onboarding projects
• Be a technical sponsor for internal engagements with Mixpanel product and engineering teams to prioritize product and systems tasks from clients

We're Looking For Someone Who Has

• 3 to 5 years of experience consulting on defining and delivering ROI through new tool implementations
• Experience working with Director-level members of the customer organization to define a strategic vision and successfully leveraging those members to deliver on that vision
• The ability to communicate with stakeholders at most levels of an organization — from talking with developers about the ins and outs of an API to talking to a Director of Data Science/Product Management about organizational efficiency
• Can manage complex projects with assorted client stakeholders, working across teams and departments to execute real change
• Has a demonstrated successful record of experience in customer success, client-facing professional services, consulting, or technical project management role
• Excellent written, analytical, and communication skills
• Strong process and/or project delivery discipline
• Eager to learn new technologies and adapt to evolving customer needs

We'd Be Extra Excited For Someone Who Has

• Experience in data querying, modeling, and transforming in at least one core tool, including SQL / dbt / Python / Business Intelligence tools / Product Analytics tools, etc.
• Familiar with databases and cloud data warehouses like Google Cloud, Amazon Redshift, Microsoft Azure, Snowflake, Databricks, etc.
• Familiar with product analytics implementation methods like SDKs, Customer Data Platforms (CDPs), Event Streaming, Reverse ETL, etc.
• Familiar with analytics best practices across business segments and verticals

#LI-Hybrid

Title: DevOps Engineer

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

Opportunity:

Responsibilities:

Infrastructure Development & Integration

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

System Optimization & Reliability

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

Compliance & Security

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

Collaboration & Agile Practices

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

Innovation & Technical Expertise

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

Requirements

Education & Experience

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

Technical Proficiency

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

Professional Skills

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

About Get Well:

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

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

About SAI Group:

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

Title: Principal Data Software Engineer

Location: Bengaluru (Bangalore)

Opportunity:

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

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

Responsibilities:

Platform Architecture & Design

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

Data Engineering & Operations

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

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

Governance, Quality & Compliance

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

Collaboration & Technical Leadership

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

Innovation & Technical Expertise

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

Requirements:

Education & Experience

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

Technical Proficiency

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

Professional Skills

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

About Get Well:

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

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

About SAI Group:

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

Why project44?  

At project44, we believe in better.  

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

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

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

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

Description:    

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

About the Role

• We are looking for a Senior Product Analyst, Data Science, to drive analytics for ML-powered products at project44.
• This role sits at the intersection of Product, Data Science, and Operations, with a mandate to define how ML systems are measured, evaluated, and improved in production. You will own the analytical frameworks that connect model performance to product outcomes, ensuring our AI capabilities deliver measurable business impact.
• You will work on ambiguous, high-impact problems, designing experiments, evaluating models (offline and online), and shaping product strategy through data. This is not a reporting role. You are expected to operate as a thought partner to Product and Data Science, influencing decisions and driving outcomes.
• As analytics evolves, this role will focus on building AI-native and agent-driven analytics systems, including semantic layers, data contexts, and automated insight generation. You will help define how analytics is consumed in an environment where agents, not just dashboards, drive decisions.

What You’ll Do

Own Product & ML Measurement

• Define and operationalize success metrics across product and ML systems, including north-star metrics, product KPIs, and model-level evaluation frameworks.

Drive Model Evaluation & Feedback Loops

• Evaluate model performance using offline and online metrics (e.g., precision/recall, lift, latency, adoption) and establish feedback loops to continuously improve models in production.

Translate Product Problems into Analytical Frameworks

• Break down ambiguous product and operational problems into structured analyses that drive clear, actionable decisions.

Partner Across Product & Data Science

• Work closely with Product Managers and Data Scientists to shape roadmaps, guide prioritization, and ensure alignment between model performance and user impact.

Build Scalable Analytics Foundations

• Develop reusable datasets (SSOTs, data marts) and enable self-serve analytics across teams.

Build AI-Native Analytics Systems

• Design and develop semantic layers, data models, and context systems that enable agent-driven analytics. Build and operationalize workflows where agents autonomously generate insights, monitor performance, and surface recommendations on a recurring basis.

Design Agent-Driven Analytics Workflows

• Design and implement agent-driven analytics workflows where insights are generated, monitored, and delivered autonomously using LLMs and modern AI tooling.

What We’re Looking For

4–6+ years in Product Analytics, Data Science, or related roles, with experience supporting data-driven product decisions.

Analytical & Statistical Expertise

Strong foundation in statistics and experimentation, including hypothesis testing, A/B testing, and causal inference.

Technical Skills

Proficiency in SQL and Python, with experience working with large-scale, event-level datasets and modern data platforms.

ML Product Understanding

Experience defining and analyzing model performance metrics and understanding trade-offs between offline and online evaluation.

Cross-Functional Collaboration

Proven ability to work closely with Product and Data Science teams to drive outcomes.

Communication & Influence

Ability to clearly communicate complex analyses and influence stakeholders across technical and non-technical audiences.

Preferred Skills

• Experience working on ML-powered products or data platforms
• Familiarity with model evaluation concepts (precision/recall, ROC, calibration, bias/variance)
• Experience analyzing online vs offline performance and feedback loops
• Familiarity with modern data stack (dbt, Snowflake/BigQuery, event tracking, feature stores)
• Experience with predictive modeling or close collaboration with Data Science teams
• Hands-on experience using AI tools (LLMs, copilots) in analytical workflows
• Experience building or working with agent-based or AI-native analytics workflows
• Familiarity with semantic layers, metrics layers, or data context systems
• Experience using LLMs for automated analysis, insight generation, or decision support
• Strong product and business intuition

What Success Looks Like (6–12 Months)

• Establish clear measurement frameworks for assigned ML-powered products
• Improve visibility into model performance and diagnostics (offline and online)
• Deliver actionable insights that influence product roadmap decisions for assigned products
• Build scalable datasets and frameworks that enable self-serve analytics
• Enable tighter feedback loops between Product, Data Science, and real-world outcomes

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

Diversity & Inclusion 

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

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

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

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

More about project44 

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

P-1348

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

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

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

The impact you will have:

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

What we look for:

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

Why project44?  

At project44, we believe in better.  

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

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

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

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

Description: 

Project44 is looking for a Data Engineer to join our engineering team. You will work in a fast-paced Agile environment designing, building, and implementing scalable micro-service systems consumed by companies around the world. 

What you’re most excited for: 

• Designing and writing ETL jobs, data monitoring, and data cleaning.  
• Building optimized data pipelines.
• Enjoy database related work: Snowflake/Postgres/MongoDB.  

• Applying software rigor to create reliable, easily extensible data systems. 
• Collaborate with product on prioritization and scheduling of product and engineering features 
• Be a positive role model. 

Requirements: 

• B.Tech/BE in Computer Science, Engineering or related field or above.  
• 3+ years of experience in SQL, schema design and data analytics.  
• Hands on in Programming proficiency in any programming language like Python(preferred), Java, Scala. 
• Experience with data system orchestration and designing pipelines 
• Experience with Agile development methodologies and supporting tools such as Jira, Confluence, Rally, etc. 
• Dynamic & driven individual with enthusiasm for working in a high-profile, fast-paced entrepreneurial environment  
• Proven track record of working in a fast paced, competing priority environment, capable of partnering with and communicating across multiple functions and teams 
• Excellent communications skills and can speak directly to executives and customers in fast-developing situations, and write critical customer communications 

Preferred Experience: 

• Experience in database administration, including Role Based Access Control (RBAC) 
• Experience with data visualization tools, e.g., Looker or Tableau 
• Understand tradeoffs and optimize towards different metrics such as cost, time, memory, or compute. 
• Develop collaborative relationships with diverse internal teams, like Sales, Infosec, Business Intelligence, or other product teams 
• Familiarity with Python, DBT, Kafka, Argo, Google Cloud, Kubernetes, Docker, and Snowflake 
• Knowledge of Real time Analytics / event driven systems 

Diversity & Inclusion  

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

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

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

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

About project44  

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

A candidate will be asked to conduct a pre-employment criminal background screening test as a standard routine to minimize moral & integrity risks among our staff and to ensure Project44 is compliant with its internal pre-employment screening policy and SOC 2, Sarbanes Oxley Act and ISO 27001 compliance. We will only ask you to conduct a criminal background check when we believe it is proportionate to the role that you will fulfil within your team and/or department   A criminal  back ground check will be facilitated by our third party vendor Accurate who will assist you to get the appropriate documents from authorities in the country where you will be employed.  Depending on the country where you will be employed your local authority will provide a Certificate of Conduct or similar document upon your request.  If there are any costs related to screening, these will be borne by Project44. When our vendor Accurate will reach out to, you will be asked for your consent. We would like to emphasize  that at all time you can decide  to withdraw from the application process and/or to withdraw the consent to perform a screening test. 

#LI-Hybrid 

About Us

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

Role Overview

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

Key Responsibilities:

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

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

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

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

What we are looking for

Must-haves:

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

What helps you stand out:

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

What We Offer

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

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

JOB TITLE: Director of Product Management, Data & Analytics

LOCATION: Bangalore, India

REPORTS TO: Chief Product Officer

Th Role

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

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

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

Responsibilities

Stabilise & Improve the Current State

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

Define the Data Lakehouse Vision

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

Build & Deliver Data Products

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

Own the AI Data Strategy

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

Lead & Grow the Team

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

Skills and Qualifications

Required Qualifications

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

Preferred Qualifications

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

About Instead

Instead is a tax platform designed to help taxpayers and tax professionals collaborate to save money on taxes. As the first company in decades to receive IRS approvals to E-file 1040, 1041, 1120, 1120S, and 1065 — we're re-inventing a complex category. Founded in 2023, Instead combines LLMs with tax law to make tax management a continuous, proactive process rather than a dreaded annual deadline.

Instead's investors include Sarah Guo from Conviction (conviction.com) and many of our customers who believe in our mission and vision. The Instead team comprises talented leaders from leading tax, financial services and fintech companies — Gusto, Intuit, Zenefits, Thomson Reuters, Wolters Kluwer, Bloomberg — as well as top tax & accounting firms such as PwC, BDO, RSM, and KPMG.

Instead was a 2024 Innovation Award Finalist in CPA Practice Advisor. Instead's CEO, Andrew Argue, is a CPA and has been named Top 100 Most Influential People in the Accounting Profession twice - Ones To Watch and CPA Practice Advisors 20 under 40.

About the role

We’re seeking an experienced Head of Data & Analytics to lead the systems, data, and reporting infrastructure that power Instead’s global operations. This role directly oversees IT Administration and Salesforce Billing Engineering, ensuring our technology stack runs securely, reliably, and at scale.

You’ll be responsible for implementing, maintaining, and optimizing our data and analytics applications, ensuring teams have the insights, automation, and secure systems they need to execute effectively. This is a hands-on leadership role and will report to our SVP of business intelligence. You will collaborate closely with teams across product, finance, sales, marketing, and engineering in India and the US, while managing day-to-day execution out of our Bangalore office.

What You'll Do

• Lead and mentor the IT Administrator and Salesforce Billing Engineer, ensuring strong performance, alignment, and growth.
• Build and manage all product reporting and dashboards through Metabase, ensuring consistency with Tableau and Salesforce reporting frameworks.
• Own the administration, optimization, and strategy for our data and analytics tools, including: Tableau, Mosyle, Dbt Cloud, Hevo Data & FiveTran, EasyDMARC, Splashtop, Zapier, Metabase, Salesforce, Zoom, Snipe-IT, Salesforce Billing & CPQ, Google G Suite, Twilio, Ninja, Slack, Docusign, Polly, Microsoft Office 365, Adobe, Loom and other apps as needed by company operations.
• Establish governance for data pipelines, reporting, and security across the company.
• Partner with finance, sales, and product to ensure accurate and integrated data flows between systems.
• Define KPIs and reporting standards, ensuring stakeholders have access to reliable, real-time insights.
• Implement and maintain strong information security measures, compliance processes, and backup/recovery protocols.
• Collaborate with US and India leadership to ensure IT, Salesforce, and analytics tools scale effectively with business growth.
  
  

What you'll need:

• 8+ years of experience in data, analytics, or systems leadership with hands-on ownership of data infrastructure and reporting tools.
• Proven experience managing and mentoring technical teams, including IT and Salesforce/RevOps roles.
• Strong technical expertise with at least several tools in our stack (Tableau, dbt, Hevo, FiveTran, Metabase, Zapier, Mosyle, EasyDMARC, Splashtop, Salesforce, Zoom, Snipe-IT, Salesforce Billing & CPQ, Google G Suite, Twilio, Ninja, Slack,
• Docusign, Polly, Microsoft Office 365, Adobe, and Loom).
• Solid background in data governance, integrations, and reporting best practices.
• Experience managing cross-functional stakeholders and aligning priorities with executive leadership.
• Excellent problem-solving, organizational, and communication skills.

Nice to have:

• Experience in fintech, SaaS, or accounting/tax technology environments.
• Familiarity with SOC 2, GDPR, or other compliance frameworks.
• Hands-on Salesforce CPQ/Billing experience.
• Prior experience in a startup or high-growth technology company.

Why join us

• Lead and scale the data, analytics, and systems foundation of a cutting-edge tax technology company.
• Oversee a critical global function spanning IT, Salesforce Billing, and business intelligence.
• Be part of a collaborative, mission-driven team.
• Competitive compensation and benefits.
• Growth opportunities in leadership, compliance, and advanced data strategy.
• Direct impact on how Instead runs, scales, and makes data-driven decisions.

Equal Opportunity Employer - M/F/D/V

As a global business, we rely on diversity of culture and thought to deliver on our goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law.

We trust our team with sensitive information, so all candidates who receive and accept employment offers must complete a background check before joining us.