Data Analytics Partner Jobs

The Data Engineering team is responsible for building ETL pipelines that populate the Internal Data Platform, which drives analytics that help the company run more efficiently. Our team builds highly performant and scalable processes that extract massive datasets and makes those datasets available for querying in an optimal way. We are looking to speak to candidates who are based in Gurgaon for our hybrid working model. What you’ll do Guide the Data Engineering team on building highly performance ETL pipelines using Spark and other Big Data technologies Help design the architecture of our Internal Data Platform to support the implementation of a robust medallion architecture Provide thought leadership on ways to achieve infrastructure cost savings on Cloud hyperscalers Design and build AI agents that can help automate many of the common development and support tasks that the team performs Work with Security and Compliance teams to ensure that datasets have appropriate permissions and regulations in place Work with our Data Platform, and Governance sibling teams to make data scalable, consumable, and discoverable We’re looking for someone with 10+ years experience working on enterprise data lakes/warehouses 5+ years of Spark and Python experience 5+ years of direct hands-on experience working with AWS or GCP Thorough AI knowledge, particularly with codegen tools and agentic frameworks Hive, Iceberg, Glue, or other technologies that expose big data as tables Familiarity with different big data file types such as Parquet, Avro, and JSON Exposure to real-time or streaming data technologies is a plus Success Measures In 3 months, you'll have a thorough understanding of the architecture of MongoDB’s internal Data and AI ecosystem In 6 months, you'll have owned the delivery of a large project from start (scoping, design) to finish (delivery) In 12 months, you'll have designed new features, led development work, and become a go-to expert on parts of the system About MongoDB

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary As a member of the Strategic Intelligence and Automation team you will be part of a nimble team that lives in and amongst data. We specialize in automating the movement of data, integrating data analysis to create new business processes, and reporting out the findings of our analysis. As part of the team you will: Build ETL workflows using Dataiku and Python to receive, manipulate and populate data Collaborate with cross-functional teams, including product managers, clinical support, and designers, to gather and document product requirements Support direct team members in testing and troubleshooting and documenting work Aid in retaining our client base by researching and resolving client issues by writing queries and analyzing data Answer internal questions by investigating the data sets Contributes to knowledge management initiatives to ensure that knowledge and best practices are understood and shared across the organization Actively contributes to team meetings, brainstorming sessions, and collaborative projects, including sharing ideas, providing feedback, and contributing to the overall goals and objectives of the team Assists in maintaining our integrated high-performance culture Required Qualifications Intermediate understanding of SQL language 2+ years experience in ETL wo

About the Team Would you like to be part of creating a unicorn within a unicorn? Solve some of the biggest challenges facing financial inclusion of Bharat? Well, then here's your chance! Financial Services (FS) is one of the biggest new bets we are taking at Meesho on the next 10x horizon opportunity for us. Just as Ant Financial did for Alibaba, and Mercado Pago did for Mercado Libre, our vision is to build financial services for Meesho, becoming our key growth and revenue driver. We have found our Product-Market Fit, built and proved 0-1 and 1-10 journeys. Now looking for someone who can be the founding member of a 10-100-1000 journey, and this is possibly one of the most exciting and enriching experiences one could consider in their career. About the Role Meesho FS runs two lines of business: SME Lending, which offers Business Loans, and User Lending, which offers BNPL and Personal Loans (PL). User Lending is now our primary focus in this phase of our FS journey. We have 274Mn ATU, and risk management is at the core of building any sustainable credit business at scale - our being a captive audience means both Growth and Risk are an outcome of underwriting, which is owned by the Risk team. Herein also lies one of our biggest challenges: how do we assess the risk of borrowers without any credit history or income data? How can we leverage alternative information to better profile borrowers? How can we leverage our platform uniquely to create a sustained competitive advantage? This person will be responsible for driving the analytics behind these questions for User Lending - creating analytical frameworks, developing high quality analysis, driving insights and actions, and recommending policy decisions, across a well-established BNPL portfolio and a Personal Loans portfolio that is still scaling. Your role will focus on: Owning the risk for one or more segments of the portfolio while maintaining a healthy growth. Analyzing credit policies using Meesho platform data,

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

Roles & Responsibilities Displays structured problem solving, application of right tools & techniques to solve open ended problems, Creates productized analytics solutions or frameworks independently. Understand Business & product problems and come up with deep data backed solutions. Root cause analysis and Deep dive analysis of certain product problems Running and maintaining the reporting system, presenting insights at a weekly forum Building templates, dashboards in Power BI, Gsheets for operational and management reporting Data extraction as per business request for Ad hoc analysis Business analysis and understanding Evaluating metrics to be tracked as per business goals, exploring other available metrics for deeper understanding of product performance Work in a fast-moving environment, across multiple projects with varying levels of complexity and detailing Desired Skills and Experience: 3 - 5 years working with large data sets and conducting quantitative analysis Some understanding of Statistics and prior experience of building statistical models (e.g. hypothesis testing, product experimentation, A/B Testing, regressions). Excellent knowledge SQL and intermediate knowledge of data manipulation language such as R/Python Previous experience with working on ecommerce funnels, retention Ability to think through product and business metrics to assess product features Knowledge of business modelling and basic knowledge of financial metrics, would be a bonus Quick learner and ability to work in dynamic work environment Team player and comfortable interacting with people from multiple disciplines Established expertise in designing new dashboards, identifying the right metrics, layout; displays proficiency in building dashboards on Power BI using best practices and intuitive Qualifications Bachelor’s in engineering, Computer Science, Economics, Statistics, or related discipline from a reputed institute ...........................

Key Responsibilities Enterprise Data Strategy & Client Engagement: Develop and maintain a comprehensive data architecture strategy that aligns with organizational and client business objectives. Serve as a key technical advisor for clients, translating business requirements into innovative data solutions. Build and maintain strong client relationships by providing expert guidance and managing expectations throughout project lifecycles. Data Modeling, Design & Engineering: Design and optimize both logical and physical data models to support enterprise-wide systems. Architect data warehousing solutions, overseeing the integration of data from multiple sources to enable robust business intelligence and analytics. Directly develop, test, and implement ETL processes and data pipelines, ensuring data quality, consistency, and performance. Technology Evaluation & Implementation: Evaluate emerging data technologies and tools to determine their fit within the existing architecture and potential for future scalability. Oversee the integration of new technologies into the enterprise data architecture, balancing innovation with risk management. Team Leadership & Hands-On Management: Lead cross-functional teams, providing mentorship and technical guidance to junior data engineers and architects. Maintain a hands-on approach by actively participating in coding, design sessions, and troubleshooting complex data issues. Ensure project milestones are met through effective resource management and team coordination. Performance, Security & Best Practices: Optimize data storage, retrieval, and processing performance across various systems. Collaborate with security teams to enforce data governance, compliance, and privacy standards. Establish and promote best practices in data management, data engineering, and architecture design. Documentation & Reporting: Develop and maintain comprehensive documentation covering data architecture designs, data flows, integrati

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We’re excited about you because... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working

Overview: We are looking for a Senior Data Engineer with deep expertise in Lakehouse architecture, real-time data streaming, cloud data infrastructure, and microservices development on Azure Kubernetes Service (AKS). You will play a central role in designing and delivering next-generation data pipelines, BI solutions, AI/ML platforms, streaming APIs, and scalable microservices that power Guidepoint's research and analytics products. This is a high-impact, hands-on engineering role. You will work closely with data architects, data scientists, analysts, frontend engineers, QA, and DevOps teams to translate complex business requirements into scalable, reliable, and observable data systems. This is a Hybrid role from our Pune office. What You'll Do: Data Engineering & Lakehouse Design, build, and maintain ETL pipelines, data ingestion workflows, and table schemas on Azure Databricks to support BI, analytics, and AI/ML use cases Architect and optimize the Lakehouse using Delta Lake on Databricks, ensuring reliability, performance, and cost efficiency Build and support data pipelines from business applications such as Salesforce, NetSuite, and other enterprise systems Develop and maintain Knowledge Graph models, entity relationship structures, and NLP-based insight pipelines Maintain data governance, data privacy standards, and compliance best practices throughout the data lifecycle Perform root cause analysis on data and processes to identify opportunities for improvement Collaborate with data architects, scientists, and business consumers to populate and optimize the data warehouse for reporting and analytics Microservices & AKS Development Develop and support scalable web APIs and microservices using Python and Azure Platform Services Build new applications, services, and platforms; optimize existing solutions and refactor legacy components using modern, scalable architec

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About Mixpanel Mixpanel turns data clarity into innovation. Trusted by more than 29,000 companies, including Workday, Pinterest, LG, and Rakuten Viber, Mixpanel’s AI-first digital analytics help teams accelerate adoption, improve retention, and ship with confidence. Powering this is an industry-leading platform that combines product and web analytics, session replay, experimentation, feature flags, and metric trees. Mixpanel delivers insights that customers trust. Visit mixpanel.com to learn more. About The Team Mixpanel Engineering is a small, fast-moving team focused on delivering real value to customers. We build powerful AI-powered product analytics while obsessing over clarity, simplicity, and delight. Engineers here own problems end to end. You can move across the stack to ship impact without being blocked by silos or heavy process. Product innovation drives our business, and product engineering teams own that responsibility. Our OLAP engine queries over 500 trillion events; a typical blob storage system we interact with processes 300 PiB/month at 1.2 Tbps sustained, and we run many of them across the world. The Data Runtime team owns the data execution layer that powers every Mixpanel product. We ensure that every customer query runs fast, cheap, and reliably, at any scale. This is an exciting time to join. Mixpanel's agentic and AI-first products are driving rapid growth in query volume, and Data Runtime is making the big bets that power it. We’re investing in elastic query compute and a distributed file cache that will let us scale query workloads dramatically without scaling cost with them. We

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of product changes. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As an Analytics Lead on the Airport team, you will collaborate with our team of engineers, product managers, and designers to conduct thorough data deep dives on airport performance, challenge our current strategy, and recommend enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product and marketplace changes, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: How should we determine pricing and earnings for airport rides? Who are our current airport drivers and what segment can we focus on to grow our supply? How does this strategy interact with driver bonuses? Which airports are underperforming and which key metrics can we use to identify and classify airport performance? What targets should we set for these key metrics and how do we efficiently monitor these metrics? What is driving high cancellation rates today and which types of riders/drivers are cancelling? What product changes can we implement to reduce cancellation rates? How are riders and drivers using different ride modes at airports, and how do we design

We are seeking a detail-oriented and analytical Data Steward – Operational Technology (OT) to join our Enterprise Data team. The ideal candidate will have a minimum of 3 to 5 years of experience in data management, data quality, and operational technology datasets. In this role, you will be responsible for managing data quality, cataloguing, asset modeling, and data standardization across operational systems (PLC, DCS, SCADA, IoT) and modern cloud data platforms like Databricks. You will work closely with plant operations, IT, data engineering, and analytics teams to ensure high data reliability, consistency, and alignment with enterprise data governance standards. Source: Adani Group | Job ID: 56028

Who We Are At Justworks, you’ll enjoy a welcoming and casual environment, great benefits, wellness program offerings, company retreats, and the ability to interact with and learn from leaders in the startup community. We work hard and care about our most prized asset - our people. We’re helping businesses get off the ground by enabling them to focus on running their business. We solve HR issues. We’re data-driven and never stop iterating. If you’d like to work in a supportive, entrepreneurial environment, are interested in building something meaningful and having fun while doing it, we’d love to hear from you. We're united by shared goals and shared motivations at Justworks. These are best summed up in our company values, which are reflected in our product and in our team. Our Values If this sounds like you, you’ll fit right in. Department Data & Analytics Who You Are You are a data leader who understands that trustworthy analytics doesn’t happen by accident — it has to be built, maintained, and governed. You think in programs, not tickets. You’re energized by the challenge of setting standards that actually stick, and you know that getting adoption requires credibility, relationship-building, and a genuine understanding of what teams need from their data. You’re as comfortable writing SQL and reviewing dbt models as you are facilitating a stakeholder alignment meeting or coaching an IC through ambiguity. You see AI tooling not as a novelty but as a practical lever for scaling work that would otherwise be prohibitively manual, and you’re already using it that way. We are seeking a highly skilled and motivated Senior Manager, Data Governance to lead Justworks’ nascent Data Governance team. This is a player-coach role : you will manage a growing team of ICs while owning the programs, standards, and cross-functional relationships that make self-serve analytics at Justworks actually work. Your team’s mandate is to set and enforce the conditions under which ana

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors As Data Scientists at Nextdoor, you will have the opportunity to influence strategic decisions with product analytics, drive better experimentation and build online and offline ML solutions. We use a semi-embedded team structure, with data team members interfacing directly with product and engineering stakeholders. The Data Science group is made up of people from a diverse set of backgrounds and perspectives, trained in fields as wide-ranging as economics, psychology, geography, physics, statistics, and operations research. We are the mathematical decision scientists for the product development organization and play a proactive and collaborative role in building and improving the product. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make As a Senior Data Scientist on the Search team, you will shape how neighbors find the people, places, posts, and business

About the Team This team builds an AI-native predictive analytics platform that embeds ML and AI-driven insights directly into production Go-To-Market workflows — powering real-time decisions at scale. The team owns the full stack from distributed data pipelines and backend services to ML and AI-powered capabilities that ship directly to customers. We are building toward a model where AI components are first-class runtime dependencies, not bolt-on features. Agentic AI development is a core part of how we increase engineering velocity and deliver customer value. This is a team that ships daily, iterates constantly, and treats speed as a capability to be deliberately improved. The Role This is a high-ownership, builder-first Sr. Software Engineer role. You will design, build, and ship AI-integrated data systems from concept through production — owning outcomes end-to-end, including deployment, monitoring, cost, and business impact. We are seeking a candidate who views AI tooling as a fundamental force multiplier in their daily engineering process. This position is central to our transition into an AI-native function, requiring an individual capable of making decisive, pragmatic architectural choices on reversible matters to maintain momentum. We need an experienced builder of production-grade, data-centric systems who is obsessed with delivering customer value and possesses a deep, curious enthusiasm for the transformative potential of AI. What You Will Build AI-Native Systems Development. Design, build, and own scalable data and ML pipelines, backend services, and AI-powered capabilities that are part of the platform's production decision-making layer. AI and ML components are runtime dependencies in this role — not research projects or experiments. Candidates will have strong back end and data engineering skills to thrive in this space. Daily Shipping. Decompose complex work into safely mergeable increments and ship them daily. Treat large, multi-day pull requ