Lead Data Analytics Engineer Jobs

About Us Tamara is a leading fintech platform in Saudi Arabia and the GCC region with a mission to help people own their dreams built on being simple, trusted, and everywhere our customers need us. Today, more than 25 million customers and over 130,000 partner merchants depend on Tamara every day for reliable financial solutions across retail, travel, education, healthcare, and beyond. Tamara is backed by Sanabil Investments, a wholly owned company of the Public Investment Fund (PIF), and SNB Capital, among others. Your Role We are looking for a Senior Data Engineer to join the team building Tamara's next-generation data core - a multi-cloud data platform spanning Event Streaming, Data Warehousing, and Experimentation. You will be hands-on; designing and operating petabyte-scale streaming and batch systems that run across clouds. This role is ideal for engineers who love solving complex data challenges at scale, think with a platform mindset, and are excited to raise the technical bar of the team around them. Your Responsibilities Lead the design and build of platform components that run across multiple clouds — addressing portability, cross-cloud replication, HA/DR, and data residency requirements of a regulated fintech environment, and designing against single-cloud lock-in. Build and operate large-scale event streaming infrastructure on Kafka, including configuration tuning and cross-cluster replication between cloud environments. Build and maintain real-time and batch data pipelines using tools like Kafka, Spark, and Airflow. Drive the development of a scalable LakeHouse architecture using modern open table formats such as Iceberg or Delta Lake. Own reliable, cost-aware operation of multi-cloud data infrastructure — SLO-based observability, data quality, and lineage. Enable Analytics and Product teams through self-serve data products, well-modeled warehouse foundations and marts, and reusable ingestion (inbound) and consumption (outbound) patterns. Provid

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 Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role We're looking for a Staff level Engineer to lead the design and development of a next-generation Data Platform at Vercel. This is a unique opportunity to architect a foundational system that will power data across our products and business, supporting everything from real-time analytics to AI/ML initiatives. Reporting directly to the Senior Director of Data Engineering, you'll define the technical vision for our data ecosystem, work across the organization to align engineering strategy with product goals, and build scalable, reliable systems using modern technologies like Kafka, ClickHouse, Tinybird, and Snowflake. You'll lead from the front, writing production-grade code, setting high standards for design and data governance, and mentoring a team of engineers as the organization grows. If you're excited by the challenge of building scalable data systems that drive product innovation, we'd love to hear from you. What You Will Do Design and implement a next-generation data platform that supports diverse requirements, including batch and real-time integrations, advanced analytics, and multiple data types, leveraging Kafka, Kafka-based tooling, and additional streaming technologies to power real-time data movement and processing. Work with engineering, product, and senior leadership teams across Vercel to architect solutions that address business needs, aligning technical strategies with product goals and ensuring seamless data availability and usability. Define and maintain guidelines for data ingestion, creation, enrichment, and stor

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

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 Product and Risk Data Engineering is Stripe's single source of truth data engineering layer for Payments, Risk, and Product — we enable Stripe to confidently run, measure, and grow the business by making accurate information easy to access. We curate and maintain high-quality data warehouses and pipelines that serve as the authoritative foundation for product and financial activity across Stripe, powering analytics, ML capabilities, agentic workflows, and merchant-facing data interfaces. Beyond building data, we act as the internal experts in data technologies and partner with Data Platform to deliver high-quality, low-friction data processing frameworks. We also serve as the bridge between data producers and data consumers — championing best-in-class data engineering practices and guiding product teams on event-driven data API modeling — so that every team at Stripe can build, decide, and grow from a trusted, well-engineered data foundation. What you’ll do We're looking for a person who could contribute to the team by solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of key tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities. Responsibilities Lead the technical outcomes for

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Senior Data Engineer, you will work to define the data ontology for all of Roblox, establish standard methodologies for data operations and lifecycle management, design and build analytics tooling and frameworks, and influence event instrumentation. Additionally, this role is highly multi-functional, requiring close collaboration with Data Science, Experimentation, and Machine Learning teams to understand customer requirements and analytics applications, as well as with Data Infrastructure and Storage teams to develop integrated solutions. Join us and be a part of a dynamic team driving innovation and growth at Roblox. This role will report to our Engineering Manager on the DSE team. You Will: Partner with Data Science, Product, and Engineering to collect requirements to define the data ontology for all of Roblox Lead and mentor a growing team of Data Engineers to support Roblox's ever-evolving data needs Design, build, and maintain efficient and reliable batch and streaming data pipelines to populate core data sets Develop scalable frameworks and tooling to automate analytics workflows and streamline users interactions with data products Establish and promote standard methodologies fo

P-988 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Lakebase enables teams to deliver applications faster with an optimized database developer experience, integration with the lakehouse, and simplified operations. It provides a managed Postgres transactional layer for application state and workloads that combine operational data, analytics, and AI. You'll join as one of the key engineers building out the Lakebase product. As the Technical Lead on the Lakebase Manager (LBM) team, you will drive, build, and operate the central control plane that owns the core logic for Lakebase: database creation and deletion, wake-up and suspend, maintaining computes on hot standby, HA failover, and more. LBM interacts with every Lakebase component (storage, compute, proxy, and console) and manages the full database lifecycle at scale, with a focus on reliability. This is a hands-on individual-contributor role: you lead the team technically and partner with the team's engineering manager, who owns people management and delivery planning. The stack is Go, Rust, PostgreSQL, and Kubernetes. The impact you will have: Set the technical direction for LBM and own the quality and reliability of what the team ships, driving execution on the hardest, highest-risk parts. Drive architecture and design, and write code on the hardest parts of your team's projects. Set and uphold high technical standards through a

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. As the Engineering Manager for the Lakehouse Foundation team, you will lead a group of engineers responsible for the foundational data layer that all of Lyft's data systems and emerging AI workloads are built on. The team owns catalog and metadata management, table formats and storage, and the access patterns and gateways through which other engineering teams interact with Lyft's data. As Lyft converges on a unified lakehouse architecture, this team builds and operates the single source of truth that powers analytics, machine learning, experimentation, and every business decision made from data. You will play a key role in shaping the team's technical direction, partnering with peer Data Platform teams on a multi-year platform evolution, and developing engineers who operate with autonomy on systems of significant scale and complexity. Lyft's Infrastructure teams build the foundational systems that the rest of engineering depends on to move fast, ship reliably, and scale efficiently. These are high-leverage roles where the work you and your team do has a multiplicative effect across the company. We're looking for experienced leaders who can balance the discipline of operating critical infrastructure with the curiosity to keep evolving how Lyft builds. Engineering at Lyft is a place where managers and engineers operate with high ownership and strong technical judgment. Our engineers expect their managers to be honest, available, and focused on the work that matters: developing their teams, removing obstacles, and giving people the support they need to do their best work. We build teams that are inclusive, technically rigorous, and have a strong sense of ownership for what they build. Responsibilities: Lead a team responsible for Lyft's foundational data layer, including catalog and metadata management,

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. 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 financial reporting. By implementing data structures and data warehouse architecture, this team serves as the foundation for decision-making at DoorDash. The focus extends to enhancing the developer experience by creating tools that support the organization's high-velocity demands. To lead the growing team of Data engineers we are looking for managers who are passionate about Data and are thought leaders in coaching, guiding and leading teams to make Data a winning edge for DoorDash. About the Role DoorDash is looking for a Data Engineering Manager to guide the development of enterprise-scale data solutions. This manager will also act as a technical expert on all things related to data architecture to empower the greater community of data engineers, data scientists, and DoorDash partners. Your focus extends to fostering an engineering culture of excellence, empowering engineers to deliver reliable, flexible solutions at scale. Additionally, you'll play a pivotal role in building and nurturing a top-performing team, driving innovation and success in a dynamic, fast-paced environment. You must be located in San Francisco, CA, Sunnyvale, CA, or Seattle, WA for this hybrid position. You’re excited about this opportunity because you will… You are a people leader. You thrive in hiring, building, growing and nurturing impactful business focused data teams You are a technology leader. You drive the technical and strategic vision for the embedded pods and foundational enablers to meet current and future needs for scale and interoperability You strive for continuous improvement of data architecture and development process You think of quick wins

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. The Fraud team at Affirm Bank works cross-functionally with Machine Learning, Product, Engineering, Operations to combat fraudulent activities to foster a safe platform. This role requires abundant cross-functional partnership. This individual will be the representative of the Credit Risk org, leading the charge on refining our Identity Verification and Fraud processes as well as our Application flow. Additionally, this role will work closely with the Product and Engineering teams to improve our Fraud solution. Come join us in our mission to change consumer finance through better technology, lower costs, and increased transparency while providing the best customer experience. What You'll Do This role will take charge of owning fraud performance for depository products, including monitoring fraud losses, approval rates, false positives, customer friction, and other key risk metrics Data Pipeline, Analytics & Monitoring Build and maintain scalable data models and transformation pipelines, using tools (such as DBT) to standardize depository product, transaction, customer, fraud, and operational data. Define trusted fraud performance metrics and analytical datasets, including fraud loss rates, approval and decline rates, false-positive rates, customer friction, and operational efficiency. Develop recurring dashboards, scorecards, and monitoring frameworks to provide clear visibility into fraud performance, portfolio health, and emerging risks. Conduct deep-dive analyses to diagnose fraud losses, control gaps, false positives, portfolio shifts, and unexpected performance changes, translating findings into actionable recommendations. Fraud Strategy Building & Optimization Develop and optimize fraud rules, policies, thresholds, models, and decision strategies

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Marketing Analytics Lead at Anthropic, you will own how we measure marketing. You'll build and run a single measurement framework that shows how marketing activity turns into pipeline, revenue, and product usage, and you'll make that framework something marketers and executives actually use to make decisions. As our marketing programs grow across enterprise and product-led motions, your work will determine whether we invest in what works. In this role, you'll own the marketing measurement framework end to end: the metric definitions, the data models behind them, the dashboards that surface them, and the insights they produce. This is a hands-on individual contributor role; data science and data engineering will support you, but you'll do the core work yourself. You'll partner closely with field marketing, partner marketing, campaign marketing, finance, sales strategy, sales development, data science, and data engineering to align on definitions and keep the whole organization working from one view of the funnel. Key responsibilities Own the marketing measurement framework that connects marketing activity to pipeline, revenue, and product usage Set the direction for the framework and extend it to programs it doesn't cover yet Define marketing metrics clearly and get cross-functional teams to agree on definitions early Build and maintain the data models that power marketing reporting Develop dashboards that marketers and executives rely on in their weekly reviews Teach marketers and executives how the metrics work, and keep teaching as the metrics evolve Lead adoption of the framework so that both marketing and execu

Join a pioneering team at the forefront of financial technology innovation. We are building a cutting-edge, agentic AI platform designed to revolutionize the end-to-end credit risk model development lifecycle. By leveraging the power of Large Language Models (LLMs) and intelligent workflows, we aim to augment our quantitative modelers, dramatically increasing their productivity, enhancing model governance, and accelerating the delivery of critical risk models. We are seeking a senior, hands-on technology leader to drive this transformation. In this role, you will partner directly with quantitative analysts and key stakeholders to shape the most impactful use cases and then lead a team of talented developers to design, build, and deploy the generative AI platform that brings this vision to life. Key Responsibilities Strategic Vision & Stakeholder Partnership: Collaborate closely with quantitative model developers, Model Risk Management (MRM), and business leaders to deeply understand their pain points and translate them into a technical vision and product roadmap. Identify, scope, and prioritize use cases for the agentic workflow platform, ensuring they deliver measurable value and align with strategic objectives. Serve as the primary technical liaison between the engineering team and its users, ensuring a tight feedback loop and continuous alignment. Platform Design & Hands-On Development: Lead the architectural design of a scalable, robust, and secure agentic AI platform, including core components for orchestration, knowledge retrieval (e.g. RAG), and tool integration. Engage in hands-on software development to build foundational components, create proofs-of-concept, and tackle the most complex technical challenges. Design and implement secure integrations with internal data sources, external APIs, and various LLMs, ensuring compliance

About the Team The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI. About the Role We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement. In this role, you will: Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas. Define the data strategy for all the data subject areas you own. Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue. Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions. Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics. Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems. Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response. Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders. You might thrive in this role if yo

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role The Threat & Analytics Lead builds GoCardless's data-driven understanding of fraud and financial crime risk. You'll bring specialist analytical expertise to both domains, helping the business understand emerging threats, measure how well existing controls are working, and identify where prevention and detection need to get stronger. Your evidence and insights will inform our strategy and how we prioritise our investments. You'll work closely with Product, Engineering, Operations and Data Science to analyse large, complex datasets and surface patterns, trends and risk concentrations across the customer lifecycle, spanning fraud prevention, transaction monitoring, sanctions screening, customer risk management and broader financial crime work. You’ll work hand-in-hand with the teams who own fraud and financial crime strategy, governance, policy and operational delivery. The Threat & Analytics Lead is a senior-level role with a high level of complexity, autonomy and expectation of impact. What excites you Getting to the root cause of problems — not just r

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. We are hiring a Staff Software Engineer to join our data platform (AAP) team in Dublin. The AAP team owns the foundational data infrastructure that powers Toast's analytics products and AI/ML capabilities: real-time streaming pipelines, a cloud-native data lakehouse, feature serving for ML-driven product experiences, and the infrastructure that enables product teams across Toast to build intelligent, data-driven experiences for our 170,000+ restaurant customers. We are in the middle of a significant platform evolution: migrating to Apache Iceberg, standing up a new Feature Store, conducting Databricks evaluations, and scaling our streaming infrastructure to meet the demands of a rapidly growing business. As a Staff Software Engineer, you'll be the technical lead for major parts of this evolution. You'll design and lead the delivery of platform capabilities that several teams depend on, doing deep hands-on work and making design calls that account for streaming, storage, serving, and the teams consuming them. You'll be the go-to expert in your area of the platform, working with product and engineering partners inside and outside our line of business. You'll make the engineers around you better through mentorship, design reviews, and the example you set. Success looks like other engineering teams moving faster because of the platform you help build. A day in the life (Responsibilities) Lead the delivery of significant data platform capabilities, from early design through production rollout, across the AAP team and the teams that depend on it Work hands-on with Kotlin/Java, Spark, Iceberg, and our streaming infrastructure, diagnosing performance, reasoning through trade-offs, and writing the code that sets the pattern for others Anticipate how requirements will change and design