Senior Data Engineer Jobs

About the Team OpenAI’s GTM Data Science team helps shape how our products are adopted, monetized, and scaled across organizations. We work at the intersection of Product, Go-to-Market, Finance, Research, and Data, turning product usage, customer evidence, and market signals into decisions that grow durable enterprise value. We’re looking for a senior Data Scientist to own the analytical strategy for enterprise knowledge-worker adoption. As ChatGPT Work and Codex become capable of research, analysis, document creation, spreadsheets, presentations, internal knowledge synthesis, and other agentic workflows, you will help determine how these products become embedded in everyday work—not merely tried once. About the Role You will define how we measure activation, retained usage, workflow depth, and value across ChatGPT Work, Codex, and connected enterprise systems. You will explain why adoption succeeds or stalls and identify the product, enablement, and commercial interventions most likely to create durable usage. This is a hands-on, zero-to-one role. You will work through imperfect telemetry, overlapping product surfaces, evolving definitions, and ambiguous business questions. You will partner closely with GTM, Product, Finance, Research, Customer Deployment, Analytics Engineering, and Data Science. Your work is successful when it changes a product, GTM, or investment decision. In This Role, You Will Define a trusted measurement framework for knowledge-worker adoption, including identity, eligible populations, activation, retained usage, penetration, workflow depth, feature adoption, and monetization. Map the knowledge-worker journey from initial exposure through first successful task, repeated workflows, multi-surface usage, and durable adoption. Identify which personas, functions, use cases, product capabilities, and account conditions are associated with deep and retained usage. Design and evaluate experiments and quasi-experiments across onboarding, enablement, wo

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About the Role We are looking for an experienced Data Steward / Senior Data Steward – Quality Excellence to help drive data quality, governance, and operational excellence across our diverse content domains. In this role, you will work horizontally across multiple content areas to establish consistent data quality standards, strengthen governance practices, identify systemic issues, and drive scalable improvements. You will partner closely with Content Operations, Product, Engineering, and Quality teams to ensure our datasets are accurate, complete, consistent, scalable, and fit for customer and AI use cases. This is a highly cross-functional role for someone who enjoys solving complex data-quality problems, bringing structure to ambiguity, and turning insights into sustainable improvements. What You'll Do Establish and maintain data quality standards, b

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies, from the world’s largest enterprises to the most ambitious startups, use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Checkout Optimization team is the growth team for Stripe’s checkout UIs. They build high-converting, personalized checkout experiences for buyers and agents, as well as the data platform that powers it. The team identifies opportunities to improve checkout through rapid product experimentation and delivers optimization at scale through our ML-powered engine. The team also builds the reliable data foundations that enable this work, including experimentation, optimization, and data-informed product decisions across Stripe’s checkout suite. Over the next 6 to 12 months, the team will focus on: Building personalized checkout experiences powered by the ML-based Optimization Engine Agentic commerce through optimizing OCS experiences for agent buyers Checkout optimization for rapidly growing AI companies Improving our data platform, which is critical to leveraging data internally and externally What you’ll do Engineering Managers at Stripe are responsible for the success of their team. You’ll be deeply involved in the engineering and design processes as well as coaching, mentoring, and leading the team. You’ll have a deep understanding of how to drive efficient engineering teams and you’ll have a strong user focus. You'll work with engineers on creating technical solutions and communicating effectively across teams and senior leadership. Responsibilities Lead and manage a team of talented full-stack product and data engineers, providing

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. Ensure Data Security, Governance, and Reliability: Implement access controls, lineage, monitoring, and compliance guardrails to support safe model training and repeatable analytics workflows.

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Smartsheet is looking for an experienced Senior Data Scientist II to build the ML models and AI sub-agents that drive growth, monetization, efficiency, and retention across the customer lifecycle. You’ll work end-to-end framing problems, building models across the modern ML and deep learning toolkit, designing sub-agents that reason and act, and shipping all of it into production for millions of users. The data is unusually rich: petabyte-scale execution data spanning two decades of how real work gets done. You are curious, technically rigorous, and can translate complex modeling and sub-agent behavior into clear recommendations for your partners. You will work primarily with Product and Engineering and will be a part of Smartsheet’s Business Intelligence team. This full-time position initially reports to the VP of Data Science located in our Bellevue, WA office, or you may work remotely from anywhere in the US where Smartsheet is a registered employer. You Will: Design and ship AI sub-agents that act across the customer lifecycle, combining predictive models, retrieved context, and LLM reasoning to recommend or take action Build the predictive and prescriptive models that power those sub-agents churn risk, growth, adoption trajectories, account health scoring, and similar lifecycle problems Develop the data foundations and knowledge layer those sub-agents reason over, applying responsible aggregation and privacy-aware design Design the tools, retrieval, and grounding strategies each sub-agent uses; decide when a s

About the Team The Finance & Supply Chain Engineering organization includes two complementary teams. Software Engineering builds internal full-stack applications, durable agentic workflows, plugins, MCPs, and measurable AI-enabled engineering practices. Data Engineering builds trusted analytics data assets for Finance and Supply Chain. The teams have distinct charters, with important shared dependencies and broad cross team partnerships across Engineering, Applications, Finance, and Supply Chain. About the Role We are looking for a hands-on senior technical leader who will report alongside the Software Engineering and Data Engineering managers. This is an individual-contributor role with no immediate people-management responsibility. The Tech Lead will raise the technical bar across both teams, participate in important cross-team or high-risk design decisions, and directly own and ship high-impact work. The role should improve team judgment and autonomy rather than act as a floating architect or universal approval gate. In this role, you will: Partner with the Software Engineering and Data Engineering managers as a peer technical leader; managers retain accountability for people, staffing, priorities, performance, and delivery commitments. Directly own the architecture, implementation, launch, and operation of one or more high-impact initiatives, remaining accountable for real outcomes rather than advisory output alone. Guide important design decisions that are cross-team, difficult to reverse, or material to security, financial controls, reliability, data quality, or long-term cost of ownership. Establish pragmatic engineering standards across architecture, APIs and data contracts, testing, security, reliability, observability, lineage, data quality, and operational ownership. Advance engineering standards for building with AI, including agentic workflows, evaluation, telemetry, adoption, and outcome measurement. Work across backend, full-stack, data, and big-d

About the Team At OpenAI, Trust & Safety Operations is central to protecting OpenAI’s platform, customers, and the public from abuse. We partner closely with Product, Engineering, Legal, Policy and Go To Market teams to identify emerging risks, build and mature enforcement systems, and ensure high-integrity operations while delivering a great user experience at scale. We’re building the Monetization Trust & Safety Operations team to ensure OpenAI can grow advertising in a way that is safe, trusted, and sustainable—for users, advertisers, and the business. This team sits at the intersection of operational scale, product risk, and rapid revenue growth, designing systems and operations that enable ads to scale without compromising user trust or safety. It’s critical to us that our Ads product be built in a way that corresponds to our Ads principles , and this team is key to that. About the Role We’re looking for a senior operator with strong analytical instincts to help build and scale Monetization Trust & Safety Operations at OpenAI. In this role, you’ll flex across the team’s highest-priority data and operational needs—from reporting and dashboard insights to budget and capacity planning, project-based analysis, and data automation —while partnering closely with Product, Policy, Engineering, Legal, Go To Market, and Data Science and Data Engineering teams. This role sits at the intersection of strategy, execution, and data: you’ll define ambiguous problems, query and validate data, build decision-support systems, and translate operational signals into clear recommendations and scalable, AI-first solutions. You should be comfortable moving from a high-level question to a rigorous analysis, a useful dashboard, an automated workflow, or a durable operating mechanism. As OpenAI introduces new revenue-generating formats and partnerships, you’ll help the team understand where risks, capacity constraints, quality gaps, and opportunities are emerging. You’ll brin

About the Role We are looking for a Senior SAP BW/BI Developer to design, build, and optimize enterprise data warehousing solutions on SAP BW. The ideal candidate has deep hands-on experience across the full SAP BW/BI stack — from data extraction and ABAP development to performance tuning and cross-platform data integration — and can independently own complex data solutions from design through production support. Key Responsibilities Design and develop SAP BW/BI solutions, including data models, extraction logic, and reporting objects to support business analytics needs. Build and maintain data ingestion pipelines from SAP ECC and functional modules including PM, FI/CO, SD, MM, and C4C into SAP BW. Develop, enhance, and debug custom extractors, user exits, and enhancements using ABAP programming. Design and build DSOs (Data Store Objects), InfoCubes, and BEx Queries to support reporting and analytics requirements. Develop and maintain APDs (Analysis Process Designer) to extract data from BW and push output files to application servers for downstream consumption. Analyze, troubleshoot, and optimize BW query and load performance, particularly for large data volumes. Build and support connectivity between SAP BW and external data platforms, preferably Cloudera and/or Google Cloud Platform (GCP). Design, schedule, and monitor Process Chains to automate data loads and ensure data availability SLAs are met. Manage Transport Requests across development, quality, and production landscapes following change management best practices. Create and maintain technical documentation, including design specs, data flow diagrams, and process runbooks. Collaborate with functional consultants, business analysts, and downstream data teams to translate business requirements into technical solutions. Provide production support, root-cause analysis, and long-term fixes for data and performance issues Requ

Job Title: Project Manager – Data & Analytics Location: Bangalore Role Overview We are looking for an experienced Project Manager to drive Agile delivery for large-scale data and analytics programs. The role requires strong expertise in Scrum, SAFe, and end-to-end delivery management, with a focus on project execution, stakeholder management, and delivering business outcomes. Key Responsibilities Drive end-to-end project/program delivery across data engineering, BI, and analytics initiatives. Act as Scrum Master and facilitate Agile ceremonies, including Sprint Planning, Daily Stand-ups, Reviews, and Retrospectives. Manage scope, timelines, risks, dependencies, and delivery quality. Lead stakeholder discussions and provide regular updates to senior leadership. Drive continuous improvement and proactively resolve project challenges. Prepare impactful PPTs, dashboards, and executive-level summaries. Work independently and ensure projects are delivered within timelines and quality standards. Required Skills & Experience 8–10+ years of progressive experience in Project/Program Management, with the majority of the career in these roles. Prior experience as a Scrum Master. Strong expertise in Agile/Scrum methodologies; SAFe experience is preferred. Excellent communication and stakeholder management skills, including with senior audiences. Strong ownership of project execution, timelines, and quality standards. Proactive problem-solving approach with the ability to take initiative and work independently. Strong presentation skills with the ability to create impactful PPTs and summarize content for senior-level discussions. Working knowledge of Databricks, Snowflake, AWS S3, and AWS Athena. Experience working in data engineering, analytics, or technology environments is preferred. Note: By submitting your application, you consent to being contacted by our Talent Acquisition team via phone call, email, SMS, WhatsApp, or other communication channels regarding your app

Senior Data Scientist (FullStack Machine Learning) About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You’ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Design, develop and deploy machine learning models and algorithms to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas. Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. Implement robust and reliable software solutions for model deployment. Set up and maintain CI/CD pipelines for automated testing and deployment. Maintain machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training. Collaborate with Platforms and Engineering to make sure the ML models built are deployed and integrated into the systems. Working with the Data Platforms teams for understanding and collecting the data. Write clean, maintainable and efficient code. Conduct performan

Senior Data Scientist (FullStack Machine Learning) About Team Myntra Data Science team delivers a large number of data science solutions for the company which are deployed at various customer touch points every quarter. The models create significant revenue and customer experience impact. The models involve real-time, near-real-time and offline solutions with varying latency requirements. The models are built using massive datasets. You will have the opportunity to be part of a rapidly growing organization and gain exposure to all the parts of a comprehensive ecommerce platform. You’ll also get to learn the intricacies of building models that serve millions of requests per second at sub second latency. The team takes pride in deploying solutions that not only leverage state of the art machine learning models like graph neural networks, diffusion models, transformers, representation learning, optimization methods and bayesian modeling but also contribute to research literature with multiple peer-reviewed research papers. Roles and Responsibilities Design, develop and deploy machine learning models and algorithms to solve complex business problems for Myntra Recsys, Search, Vision, SCM, Pricing, Forecasting, Trend and Virality prediction, Gen AI and other areas. Theoretical understanding and practice of machine learning and expertise in one or more of the topics, such as, NLP, Computer Vision, recommender systems and Optimisation. Implement robust and reliable software solutions for model deployment. Set up and maintain CI/CD pipelines for automated testing and deployment. Maintain machine learning pipelines, contributing to tasks like data cleaning, feature extraction and basic model training. Collaborate with Platforms and Engineering to make sure the ML models built are deployed and integrated into the systems. Working with the Data Platforms teams for understanding and collecting the data. Write clean, maintainable and efficient code. Conduct performan

About the Company: Sigmoid enables business transformation using data and analytics, leveraging real-time insights to make accurate and fast business decisions by building modern data architecture using cloud and open-source technologies. Some of the world’s largest data producers engage with Sigmoid to solve complex business problems. Sigmoid brings deep expertise in data engineering, predictive analytics, artificial intelligence, and DataOps. Offices: New York | Dallas | San Francisco | Lima | Bengaluru. The role below is for our Bengaluru office. Why Join Sigmoid? Sigmoid provides the opportunity to push the boundaries of what is possible by seamlessly combining technical expertise and creativity to tackle complex business problems and convert them into straightforward data solutions. You will work in a fast-paced, high-impact environment and help shape data, analytics, and AI-led transformation for leading global insurance enterprises. About the Role: Sigmoid is looking to board a Leader for our Insurance Consulting Practice who can bridge the gap between high-level strategy and granular operational reality. A true expert in the insurance space must understand the interconnectedness of insurance products, claims ecosystems, underwriting dynamics, customer journeys, regulatory requirements, and operational processes. In this role, you will drive strategic initiatives, foster innovation, and provide visionary direction to our insurance practice with a strong focus on insurance analytics and AI-led transformation. The role requires a strong portfolio leader responsible for managing strategic accounts across new business development and account growth, while partnering with senior client stakeholders to define analytics use cases across Data Engineering, Data Science, Product Engineering, and Consulting. Roles and Responsibilities: Strong understanding of Insurance sub sectors operating model, value drivers and underlying mechanics Insurance Operations - Ability to

About Sigmoid Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best-in-class end-to-end data value chain capabilities spanning Data Science, Data Engineering, and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team-first mindset. You'll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices: New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. Role: Associate Director - Delivery About the Role You will lead delivery for large-scale Data Engineering programs, working closely with clients to architect and drive execution of modern data platforms - data pipelines, cloud migrations, lakehouse implementations, and real-time data processing solutions. You will own end-to-end delivery governance across multiple engagements, act as a senior escalation point for clients, and provide technical and delivery leadership to teams building enterprise-grade data engineering solutions. If you enjoy operating at the intersection of technical depth in Data Engineering and delivery leadership, we would like to talk to you. Required Skills & Competencies 15-18 years of experience in Project Delivery, Client Engagement, or Data Engineering Delivery Management, with a significant portion focused on Data Engineering programs. Strong hands-on exposure to Data Engineering tools and technologies, including cloud data platforms Proven experience in Analytics/Consulting/IT Services, managing complex Data Engineering project execution, architecture reviews, and governance. Exposure to US/Global clients, with experience handling client escalations. Ability to manage multiple Data Engineering project teams and pods, mentor Delivery/Engineering Managers and technical leads, and drive engineering process improveme