Analytical Engineer Salary India Jobs

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.

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 Finance and Strategy team is an integral thought partner to Stripe's core functional leaders. We bring understanding and predictability to Stripe's bottom line financials. We work cross-functionally across many surfaces at Stripe and help steward Stripe's resource investments to improve the durability of our long term financial performance. What you'll do We're looking for a Finance and Strategy Partner to join our growing team. You'll help with forecasting, budgeting, and reporting for various departments accurately and in a timely manner and deliver improvements in our integrated financial systems with business partners, financial colleagues, and engineers. Responsibilities Partner closely with business leaders to support and influence key strategic and business decisions, serving as their financial partner for analysis and evaluation of strategic projects and initiatives (e.g., foundational investments or business model shifts) Design and provide analytical rigor to measure efficiency and ROI of investments in headcount and non-headcount expenses Drive reporting, process, and discipline for finance routines to shape and influence decision-making (e.g., budget, forecast, monthly reviews, and long-range plans) Build and own models for in-depth analyses, ensuring their quality, timeliness, and accuracy Define metrics, leading indicators, and reporting dashboards in partnership with cross-functional teams such as Data Science Drive contin

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 Finance and Strategy team is an integral thought partner to Stripe's core functional leaders. We bring understanding and predictability to Stripe's bottom-line financials. We work cross-functionally across many surfaces at Stripe and help steward Stripe's resource investments to improve the durability of our long-term financial performance. What you'll do We're looking for a Finance and Strategy Analyst to join our growing teams on the Go-to-Market (GTM) and Partnerships teams. You'll help us with the forecasting, budgeting, and reporting for various departments accurately and in a timely manner and deliver improvements in our integrated financial systems with business partners, financial colleagues, and engineers. Responsibilities • Leverage your financial background to support and influence key strategic and business decisions • Design and provide analytical rigor to measure efficiency and ROI of investments in headcount and non-headcount expenses • Drive reporting, process, and discipline for finance routines to shape and influence decision-making (e.g. budget, forecast, monthly reviews, long-range plans) • Build and own models for in-depth analyses, as well as ensure their quality, timeliness, and accuracy • Define metrics and leading indicators of business performance • Partner with cross-functional teams, such as Data Science, to develop reporting dashboards • Drive continuous process improvement, standardization, simplification, a

Job Overview We are looking for an Analytics Engineer who will own dbt Cloud in our organisation and maintain the analytics pipelines built on top of it. You will administer dbt Cloud across multiple independent projects, keep our business-critical pipelines running (including finance data models), and support analysts in other teams as a mentor and go-to person for dbt. Our stack is Snowflake, dbt and AWS, with Python for tooling and automation. We are also building AI-assisted and agentic workflows into our daily work, and you will take an active part in this. Reports to Director of Mobile and New Games What will you do? Administer dbt Cloud for the whole organisation: project setup, environments, permissions, CI/CD, version upgrades and cost control Set up and support multiple independent dbt projects, define common standards and conventions so teams stay aligned Develop and maintain production dbt pipelines, including complex finance models where accuracy and trust are critical Mentor analysts on dbt, SQL modeling, testing and code review Tune Snowflake performance and cost, improve pipeline reliability and monitoring Build tooling and automation in Python (AWS Lambda, S3, orchestration, metadata workflows) Drive AI adoption in our analytics engineering work: build common AI skills for dbt development (documentation, testing, code generation) and automated agentic workflows that the whole team can reuse Follow current trends in AI tooling and agentic systems, evaluate new approaches and bring the useful ones into the team What are we looking for? 4+ years of experience in analytics engineering, data engineering or a similar role Strong hands-on dbt experience, ideally including dbt Cloud administration (projects, environments, jobs, CI/CD), not only model development Strong SQL and data modeling skills Production experience with Snowflake, including performance tuning and cost awareness Python for data tooling and automation Experience with AWS services used in

Job Overview We are looking for an Analytics Engineer who will own dbt Cloud in our organisation and maintain the analytics pipelines built on top of it. You will administer dbt Cloud across multiple independent projects, keep our business-critical pipelines running (including finance data models), and support analysts in other teams as a mentor and go-to person for dbt. Our stack is Snowflake, dbt and AWS, with Python for tooling and automation. We are also building AI-assisted and agentic workflows into our daily work, and you will take an active part in this. Reports to Director of Mobile and New Games What will you do? Administer dbt Cloud for the whole organisation: project setup, environments, permissions, CI/CD, version upgrades and cost control Set up and support multiple independent dbt projects, define common standards and conventions so teams stay aligned Develop and maintain production dbt pipelines, including complex finance models where accuracy and trust are critical Mentor analysts on dbt, SQL modeling, testing and code review Tune Snowflake performance and cost, improve pipeline reliability and monitoring Build tooling and automation in Python (AWS Lambda, S3, orchestration, metadata workflows) Drive AI adoption in our analytics engineering work: build common AI skills for dbt development (documentation, testing, code generation) and automated agentic workflows that the whole team can reuse Follow current trends in AI tooling and agentic systems, evaluate new approaches and bring the useful ones into the team What are we looking for? 4+ years of experience in analytics engineering, data engineering or a similar role Strong hands-on dbt experience, ideally including dbt Cloud administration (projects, environments, jobs, CI/CD), not only model development Strong SQL and data modeling skills Production experience with Snowflake, including performance tuning and cost awareness Python for data tooling and automation Experience with AWS services used in

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building a single source of truth for financial information using dbt and Snowflake to enable scalable BI and process automation across the org. We are hiring an Analytics Engineer focused on maintaining and optimizing our finance data platform , improving reliability, efficiency, and performance of our pipelines and core datasets. This role is ideal for someone who enjoys operational ownership, building strong foundations, and making data systems easier and safer to run at scale. What You’ll Do Build and maintain dbt models and core datasets that support Accounting reporting and downstream automation use cases. Improve platform reliability through strong testing patterns, alerting, and runbooks. Own and document data pipelines and lineage, ensuring changes are understandable and auditable. Identify, troubleshoot, and resolve production data issues, and drive root-cause fixes. Optimize performance and cost in Snowflake and dbt to support scaling needs. Partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets. Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows). What We Look For 3+ years of experience in analytics engineering, data engineering, or similar roles working with production data systems. Strong SQL skills and hands-on experience building in dbt (modeling, testing, documentation). Experience operating in a modern development workflow: Git and pull-request based collaboration (GitHub preferred). Familiarity with standard IDEs and collaborative debugging practices. E

#Team Nextdoor Nextdoor is where you connect to the neighborhoods that matter to you so you can belong. Our purpose is to cultivate a kinder world where everyone has a neighborhood they can rely on. Neighbors around the world turn to Nextdoor daily to receive trusted information, give and get help, get things done, and build real-world connections with those nearby — neighbors, businesses, and public services. Today, neighbors rely on Nextdoor in more than 350,000 neighborhoods across 11 countries. Meet your Future Neighbors As an Analytics Engineer 4 with Nextdoor, Inc. (San Francisco, CA) (May telecommute from any U.S. location) you’ll: Apply mathematical or statistical theory and methods to design, create, and select the appropriate samples of data that will allow the data science team to conduct probabilistic experiments and statistical analyses Design software systems and processes to gather data in the most efficient way and determine key data points needed in order to interpret experiment results and ensure results are properly tracked Interpret data and report conclusions drawn from their analyses Work with cross-functional teams, including product, design, engineering, marketing, operations, and sales, to determine which data analyses will lead to the most actionable insights Build data pipelines to create and transform data for analysis of different product features Clean and summarize data to make it accessible for reporting and for data science Combine data from multiple sources to make and distribute client reports in order to see how particular ad products are performing Analyze expected vs actual delivery of ad products in order to find and improve gaps in our delivery pipeline What You’ll Bring to The House Master’s degree or foreign equivalent in Mathematics, Statistics, Business Analytics, or closely related quantitative field. Three (3) years of years of experience in the role or in a related position. Full term of experience m

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Marketing Enablement & Technology (MET) team sits natively within Instacart's Marketing organization, owning the data foundations that power Paid Marketing, SEO, and Retailer Marketing attribution. These datasets directly inform how we allocate hundreds of millions of dollars in marketing spend and how we measure growth. We're hiring an Analytics Engineer II to help build and evolve the marketing analytics data foundation. In this role, you'll independently design and deliver high-quality, business-aware data models and pipelines that Data Scientists and Analysts trust — owning your work end-to-end, raising the quality bar through code reviews and design discussion, and growing toward broader technical ownership of marketing data. About the Job Marketing Analytics Data Development: Independently build and maintain high-quality dimensional dat

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ ➡️ Mission: Join us as Analytics Engineer x Business Analytics and become the person our Business Analytics teams can build on without a second thought. You will own end-to-end the data models feeding Product, Growth, and Ops Finance analytics — designing scalable dbt models, pushing back on requests that would trade reliability for speed, and helping the team migrate to Omni and a real semantic layer. You will work closely with Jules Jeanroy, our Analytics Engineering Manager, and partner daily with Business Analysts across Product, Growth, and Ops Finance. The team is at a pivotal moment — investing in scalability, cutting technical debt, and building the standards that will define how Analytics Engineering works at Qonto for years to come. ➡️ As an Analyti

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. The Data team works across Linear, supporting Product, Engineering, and GTM. We own our data pipelines, warehouse, dashboards, analysis, and integrations with third-party tools. As a small team, we focus on building systems that make data accessible and useful across Linear. We’re looking for someone who wants to help shape how we architect, build, and use data as we grow. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North America. You can work from anywhere within this region. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you’ll do Work across Product and GTM (Marketing, Sales, Customer Success, and Finance) to turn ambiguous questions and operational needs into useful metrics, models, analyses, and workflows Build and maintain dbt models and pipelines that create trusted views of our product, customers, and business Design clear, maintainable data models and improve the testing, documentation, performance, and reliability of our data stack Build dashboards and self-service reporting in Metabase and Hex, and dig deeper when the answer requires more than a chart Operationalize data through reverse ETL and partner with GTM Engineering on the scoring, segmentation, a

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. Learn more about OpenAI’s approach to safety About the Role As an Analytics Engineer in Safety Systems, you will play a pivotal role in building a data-centric culture, enhancing decision-making processes, and driving strategic initiatives through analytics. You will partner closely with Engineering, Research, and Data Science to develop and maintain canonical data sources and source-of-truth dashboards that enable both people and AI agents across the organization to derive trustworthy, actionable insights. You will own the consumption layer for safety metrics: defining intuitive, reliable ways for stakeholders across Safety Systems, partner teams, and leadership to understand the safety of our products, answer safety-related questions independently, and inform product decisions and company strategy. Most importantly, you will be a core member of the Safety Systems team, collaborating with researchers and engineers to advance our goals of safe, robust, and reliable AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and maintain canonical datasets that serve as sources of truth for safety metrics. Develop and refine data products such as dashboards, reports, agent-enabled workflows, and machine-readable interfaces that empower stakeholders to extract and analyze data independently. Work closely with stakeholders in Engineering, Research, and Data Science to understand their decision-making n

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About Snowflake Snowflake started with a clear vision: develop a cloud data platform that is effective, affordable, and accessible to all data users. Snowflake developed an innovative new product with a built-for-the-cloud architecture that combines the power of data warehousing, the flexibility of big data platforms, and the elasticity of the cloud at a fraction of the cost of traditional solutions. We are now a global, world-class organization with offices in more than a dozen countries and serving many more. This role requires in-person attendance in our Pune office at least 3 days per week. Job Description We are looking for an Analytics Engineer to join our growing Finance Analytics Engineering team. In this role, you will drive value and empower decision-making by developing and maintaining the data infrastructure which fuels reporting and analysis for the Finance organization and has a direct impact on Snowflake’s success as a company. As an Analytics Engineer, you will be responsible for the following: Use SQL, Python, Snowflake, dbt, Airflow, and other systems while working within an agile development model to build and maintain data infrastructure for use in reporting, analysis, and automation Perform data QA and develop automated testing procedures for use with S

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE SHOULD YOU ACCEPT THIS CHALLENGE… The GTM BI team at Pure Storage supports Revenue Operations across pipeline, forecasting, seller performance, and executive reporting — and we are at an inflection point. We are midway through a strategic migration to dbt as our transformation standard. Beyond that, our roadmap includes scalable automation frameworks, semantic business intelligence, and AI-enabled workflows that help surface insights with less manual effort. As a Senior Analytics Engineer, you will help drive that journey end-to-end. This role is grounded in modernization first: building scalable dbt foundations, improving quality and engineering standards, and enabling the team to operate more efficiently before scaling broader AI-enabled capabilities. You will partner closely with BI analysts, Sales Operations, Systems teams, and backend engineering partners to modernize how analytics is engineered, governed, and consumed across the organization. This role is for someone who wants to build — not maintain. WHAT YOU’LL DO… Lead and contribute hands-on to the team’s dbt and Snowflake modernization initiatives Build scalable semantic and metrics layers supporting GTM domains including pipeline, forecasting, quota, attainment, and seller performance Design and maintain robust ELT/ETL pipelines, orchestration workflows, and reusable business-facing datasets Build CI/CD, testing, observability, lineage, and data qualit

Job Description: Data & Analytics Engineer (3-4 Years Experience) : 100% Remote Job Title: Data & Analytics Engineer Experience: 3-4 years Location: Remote Employment Type: Full-time Team: Data Engineering & Analytics About the Role Eltropy is a digital conversations platform for credit unions and community financial institutions in the US. The Data Engineering & Analytics team builds the AWS data pipelines and customer-facing dashboards that power analytics across the platform. We are looking for a Data & Analytics Engineer with 3-4 years of experience who can own dashboard delivery end to end along with the pipelines behind it. The ideal candidate learns fast, builds product context quickly, listens well, and collaborates effectively across product, engineering, DevOps, and customer-facing teams. Key Responsibilities Own dashboard changes end to end in QuickSight and ThoughtSpot - new metrics and filters, SPICE refresh management, internal-to-production promotion, and post-release validation. Build and maintain batch and streaming ETL pipelines on AWS using Glue (PySpark), S3, Redshift, and Airflow (MWAA) DAGs. Write and optimize Redshift SQL; debug query performance, connection contention, and data mismatches across sources. Support near-real-time ingestion (Kafka/MSK CDC → Glue Streaming → S3 → Redshift). Investigate customer-reported analytics discrepancies (Jira/support tickets), root-cause them in the data, and communicate findings clearly to support, product, and engineering. Set up and respond to pipeline monitoring - CloudWatch metrics and alarms, monitoring DAGs, refresh health - and participate in incident triage and RCA. Develop deep product knowledge: understand what each metric means to our credit union customers and translate product changes into data model and dashboard updates. Ensure data quality, validation, and consistency across systems. Required Skills & Qualifications 3-4 years of experience in data engineering and/or