Data Engineer Jobs

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . The Data Product Platform is mission-critical to accelerating data-driven decision-making at Pinterest on the foundation of 100s of thousands of tables and an exadata-scale data warehouse. We strive to provide effortless, efficient, and reliable data products and platforms that power the entire company. We achieve this by investing in three core areas: Data Warehouse: Building and managing the foundational data warehouses that enable key analyses across both our core engagement and monetization products. Analytical Velocity: Creating powerful analytical tools that empower internal data users to leverage our vast data assets and capable infrastructure effectively. Data Governance: Defining and implementing the data governance policies and tools necessary to ensure the responsible, efficient and compliant storage and handling of all data. We are s

ABOUT THE ROLE Peloton is looking for a talented Data Engineering Manager to join the Data Engineering team. In this role, you will lead the DataOps function, driving operational excellence across our data platforms while managing the successful delivery of data initiatives through a combination of internal and offshore engineering resources. You will work closely with business stakeholders, engineering teams, analytics partners, and platform owners to ensure our data ecosystem remains reliable, scalable, and well-governed. This role combines technical leadership, operational management, and stakeholder engagement, to help support Peloton's growing data and AI needs. This role will be hybrid, not remote. YOUR DAILY IMPACT AT PELOTON Lead the DataOps function within the Data Engineering team, driving operational maturity, platform reliability, and process improvements Manage and mentor offshore engineering resources, providing technical guidance, performance feedback, and delivery oversight Partner with stakeholders across multiple business functions to gather requirements, prioritize work, and ensure successful delivery of data solutions Own intake, prioritization, and execution processes for DataOps requests and operational support activities Drive adoption of data engineering standards, ETL best practices, documentation requirements, and operational procedures Serve as an operational owner for key data platforms, including Airflow, Airbyte, and Looker, owning platform governance activities such as user access reviews, compliance reviews, audit support, and operational controls Coordinate incident management, root cause analysis, monitoring, alerting, and operational readiness efforts across the data platform Help shape the long-term operating model for the Data Engineering team as Peloton continues to scale its data and AI initiatives YOU BRING TO PELOTON 5+ years of experience in data engineering, analytics engineering, software engineering, or related technical

Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We are looking for an experienced Data Engineer to partner with our Data Science and Data Infrastructure teams to own and scale our data pipelines. You’ll also work closely with stakeholders across business teams including sales, marketing, and finance to ensure that the data they need arrives promptly and reliably. You’ll play an integral role in building the metrics and self-serve reporting capabilities to unlock Figma’s next phase of growth. This is a great role for an individual who is passionate about working with data and data systems, and who love s solving problems. You’ll have a good sense for when it makes sense to build fast, scrappy solution s to unblock a key stakeholder vs. when to push back or bring in an outside service. The ideal candidate will be a great communicator who can help coordinate across multiple internal and external teams and take s pride in building end-to-end projects. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma : Own, build, and maintai n scalable data pipelines that connect various cloud data sources. Develop a deep understanding of Figma’s core data model s and optimize data pipelines for scale. Partner with the Data Science and Data Infrastructure teams to build new foundational data sets that are trusted, well understood, and enable self-service . Work with a wide range of cross-functional stakeholders to derive requirements and architect shared datasets; ability to documen

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. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games. Discord is looking for an experienced and passionate Data Engineer, Analytics to join our data team! You will be owning the transformation and semantic layer that turns data into clean, tested, well-documented tables and dashboards that data scientists, product managers, and business stakeholders can trust and self-serve from. You'll define and operationalize the metrics that inform how we identify opportunities, measure success, and make decisions. If this sounds exciting to you and you’re passionate about data modeling, metric design, and empowering teams to move faster with reliable data, read on! What you will be doing : Design, build, and maintain curated analytical datasets and data models that serve as canonical sources for metrics, dashboards, and analyses Own metric definitions end to end, from partnering with data science and product team to define what we should measure, to implementing it in production, to surfacing it in visualization tools Build and maintain executive-level dashboards and self-serve reporting tools that enable business stakeholders to answer their own questions Partner closely with data science, product manager, and engineering teams to translate business questions into well modeled, performant, and discoverable data assets Establish and enforce data quality standards through testing frameworks, documentation, and monitoring for the datasets you own Drive adoption of consistent data modeling patterns, naming conventions, and documentation norms across the data organization What you should have 3+ years of experience in analytics or data engineering with a strong focus on b

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Through a combination of strategic partnerships and self-built campuses, we are scaling the compute, storage, and networking platforms that power frontier AI training and inference. The Scaling Analytics team builds the data and software systems that help Industrial Compute understand, plan, and operate infrastructure at global scale. We work across capacity, hardware, storage, infrastructure software, and operational systems to connect fragmented sources of infrastructure data and make that information reliable and usable for engineering and planning. As OpenAI's infrastructure footprint grows, CPU and storage data increasingly spans internal platforms, vendor systems, APIs, databases, object storage, capacity management systems, and operational tooling. Building reliable connections across these environments is critical to understanding available capacity, utilization, fleet state, and infrastructure growth. About the Role We are seeking a Data Engineer to build the data systems and integrations that connect OpenAI's CPU, storage, and supporting infrastructure platforms. This role sits at the intersection of data engineering and backend software engineering. Rather than focusing primarily on traditional analytical pipelines, you will build the software and integrations required to collect, normalize, and make infrastructure data available across a heterogeneous set of systems. CPU and storage data may originate from internal infrastructure platforms, vendor APIs, databases, object storage, capacity systems, and operational services. You will determine how to reliably connect these systems and where those integrations should live—whether within an existing infrastructure service, an orchestration framework, a scheduled workload, or a purpose-built application. You will work closely with Infrastructure Engineering, Capacity Engineering, Storage,

About the Team OpenAI, in close collaboration with our capital partners, is building the world's most advanced AI infrastructure ecosystem. The Scaling Analytics team serves as the data backbone for this effort, enabling leaders and operators to make informed decisions across infrastructure deployment, hardware operations, supply chain, capacity planning, and site execution. As OpenAI’s Industrial Compute expands across an increasing number of global data center campuses, the complexity of managing infrastructure capacity, hardware health, supply flows, and operational performance continues to grow. Scaling Analytics develops the data models, pipelines, metrics, and reporting systems that transform fragmented operational data into actionable insights, helping OpenAI operate infrastructure at unprecedented scale. About the Role We are seeking a Data Engineer to help build and scale the analytical foundations that power OpenAI's infrastructure organization. This individual will partner closely with Hardware Operations, Capacity Planning, Supply Chain, Infrastructure Delivery, Finance, and Engineering teams to create reliable data products that support critical operational and strategic decisions. Today, much of the team's expertise is concentrated within several highly specialized domains including hardware health, GPU attribution, and supply analytics. As Stargate grows and new sites come online, the demand for analytics support continues to expand across both existing and emerging problem spaces. This role will increase the team's ability to move quickly, reduce operational bottlenecks, and provide additional depth across critical infrastructure analytics functions. The ideal candidate combines strong data engineering fundamentals with an ability to navigate ambiguous operational environments, translating complex infrastructure problems into scalable data solutions that improve visibility, decision-making, and execution. Key Responsibilities Design, build, and maint

About the team The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement robust and fault-tolerant systems for data ingestion and processing. Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear. Ensure the security, integrity, and compliance of data according to industry and company standards. You might thrive in this role if you: Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering). Proficiency in at least one programming language commonl

About the Team The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the role: We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI! In this role, you will: Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse. Develop canonical datasets to track key product metrics including user growth, engagement, and revenue. Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions. Implement ro

About the Team At OpenAI, we’re building the connective tissue between our mission and our people. People Innovation Labs is a fast-moving engineering team embedded in the People organization, focused on rethinking how we find and retain the best talent and empower everyone to do their best work. From recruiting to culture, we’re designing systems that give our People Team a significant edge by infusing OpenAI’s models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We’re defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation. About the Role We’re seeking a Data Engineer to build data-intensive systems that will power People Innovation Labs’ internal products and enable the People Analytics function to do their best work. These data pipelines are crucial for our build-out of people products backed by business systems of record and for ongoing people data analytics. One example of an employee-facing product you’ll help us build is OpenHouse, which serves as a culture and communication hub and an organization-wide front door into all other aspects of People Innovation Labs’ work. OpenHouse and other products in our portfolio are built by full stack product engineers who are deeply curious about culture, recruiting and people development, and want to know everything from the business strategy and metrics down through the code that gets us there. In this role, you will work with People Innovation Labs leadership and software engineers and the People Analytics team to build the data systems that enable this work. In this role, you will: Design, build and manage people data pipelines, ensuring all data is seamlessly integrated into our Databricks warehouse. Develop canonical datasets to track key people metrics and People Innovation Labs produc

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Full Stack Data Engineer is responsible for designing, developing, supporting, and enhancing Trade Operations applications, data pipelines, and cloud-based services that power the end-to-end Trade data lifecycle. This role combines software engineering, data engineering, cloud technologies, and operational support to ensure Trade data is processed accurately, securely, and efficiently from ingestion through product delivery. The engineer will partner closely with Trade Operations Analysts and Technology teams to build scalable solutions, automate manual processes, improve data quality, modernize legacy platforms, and support strategic initiatives such as market onboarding, cloud migration, and AI-driven process improvements.

Data Engineering – Technical Lead About Us: Paytm is India’s leading digital payments and financial services company, which is focused on driving consumers and merchants to its platform by offering them a variety of payment use cases. To merchants, Paytm offers acquiring devices like Soundbox, EDC, QR and Payment Gateway where payment aggregation is done through PPI and also other banks’ financial instruments. To further enhance merchants’ business, Paytm offers merchants commerce services through advertising and Paytm Mini app store. Operating on this platform leverage, the company then offers credit services such as merchant loans, personal loans and BNPL, sourced by its financial partners. About the Role: This position requires someone to work on complex technical projects and closely work with peers in an innovative and fast-paced environment. For this role, we require someone with a strong product design sense & specialized in Hadoop and Spark technologies. Requirements: 4 to 8 years of experience in Big Data technologies. The position Grow our analytics capabilities with faster, more reliable tools, handling petabytes of data every day. Brainstorm and create new platforms that can help in our quest to make available to cluster users in all shapes and forms, with low latency and horizontal scalability. Make changes to our diagnosing any problems across the entire technical stack. Design and develop a real-time events pipeline for Data ingestion for real-time dash- boarding.Develop complex and efficient functions to transform raw data sources into powerful, reliable components of our data lake. Design & implement new components and various emerging technologies in Hadoop Eco- System, and successful execution of various projects. Be a brand ambassador for Paytm – Stay Hungry, Stay Humble, Stay Relevant! Skills that will help you succeed in this role: Fluent with Strong hands-on experience with Hadoop, MapReduce, Hive, Spark, PySpark etc.Excellent progr

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Job Summary: Build systems for collection & transformation of complex data sets for use in production systems Collaborate with engineers on building & maintaining back-end services Implement data schema and data management improvements for scale and performance Provide insights into key performance indicators for the product and customer usage Serve as team's authority on data infrastructure, privacy controls and data security Collaborate with appropriate stakeholders to understand user requirements Support efforts for continuous improvement, metrics and test automation Maintain operations of live service as issues arise on a rotational, on-call basis Verify whether data architecture meets security and compliance requirements and expectations .Should be able to fast learn and quickly adapt at rapid pace. java/scala, SQL, Minimum Qualifications: Bachelor's degree in computer science, computer engineering or a related field, or equivalent Experience 6+ years of progressive experience demonstrating strong architecture, programming and engineering skills. Firm grasp of data structures, algorithms with fluency in programming languages like Java, Python, Scala. Strong SQL language and should be able to write complex queries. Strong Airflow like orchestration tools. Demonstrated ability to lead, partner, and collaborate cross functionally across many engineering organizations Experience with streaming technologies such as Apache Spark, Kafka, Flink. Backend experience including Apache Cassandra, MongoDB and relational databases such as Oracle, PostgreSQL AWS/GCP Solid hands on with 4+ years of experience. St

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