Senior Data Engineer Jobs

Opportunity Overview: This is a unique opportunity to join a high-caliber software engineering team that is growing quickly. You will play a key role in building impactful healthcare technology on a modern technology stack, with a focus on our core data and AI platforms. Your work will focus on enhancing the platform's key features, while also balancing scalability, reusability, and performance. Role Overview: We're looking for a Staff Platform Engineer to serve as the technical backbone of our Engineering organization. You'll own the technical strategy, and delivery of our platform — spanning architecture, DevOps, SRE, security, Dev-ex. This is a hands-on staff level role: you'll set technical direction, drive cross-team alignment, and be the senior escalation point for platform challenges. What you’ll do: Drive platform reliability, scalability, security, and cost efficiency across all environments. Technical Leadership: Provide technical leadership for platform components, Influence the technical strategy and architecture of our cloud platform, from CI/CD pipelines to observability and incident response. Design and implement platform components and reusable integration patterns that minimize custom development efforts, reduce the time spent on repetitive tasks, and ensure that integrations scale across multiple healthcare systems Partner closely with Architecture, DevOps, SRE, and Security teams to deliver cohesive platform solutions Cross-Functional Collaboration: Work closely with product teams, and solutions architects to understand integration needs and ensure the platform meets current and future business requirements. Serve as a senior escalation point for infrastructure and platform incidents Establish frameworks for: AI governance and compliance. Observability of systems. Traceability of decisions and outputs. Ensure enterprise readiness with security, auditability, and reliability in production environments. Security & Compliance : Ensure all p

Opportunity Overview: This is a unique opportunity to join a high-caliber software engineering team that is experiencing rapid growth. You’ll play a key role in building impactful healthcare technology on a modern technology stack, with a focus on our core data and AI platforms. Your work will focus on enhancing the platform's key features, while also balancing scalability, reusability, and performance. As a Staff Engineer on the Application Engineering team, you’ll serve as a senior technical leader - responsible for designing and delivering high-quality, scalable software systems that power Cohere Health’s core platform. You’ll act as a multiplier, elevating the technical bar for the team, mentoring engineers, and partnering with product, data, and clinical teams to deliver solutions that meet compliance, quality, and performance standards. This role is ideal for engineers who thrive on solving complex problems in healthcare, have deep expertise in building distributed systems, and want to influence architecture and engineering practices at scale. What you’ll do: Technical Leadership & Architecture Define and drive the architecture of large-scale, distributed application systems across the Cohere platform. Ensure solutions are secure, performant, maintainable, and compliant with NCQA, CMS, and payer requirements. Champion engineering best practices in CI/CD, testing, release management, and observability. Hands-On Engineering Write clean, maintainable, and well-tested code, primarily in modern frameworks (e.g., Python, TypeScript/React, Java/Kotlin). Lead the development of core features and APIs that directly impact providers, payers, and patients. Partner with DevOps and Data teams to ensure seamless integration, scalability, and operational readiness. Quality & Compliance Focus Embed automated testing, monitoring, and release safeguards into the development lifecycle. Proactively address compliance and audit-readiness requirements in application

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection, error outliers and faulty deployment analysis. As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performa

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC , VISUAL, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. What You'll Be Doing: Contribute to the development of open-source inference frameworks such as SGLang and vLLM, including feature and operator development, performance optimization, and model support, in collaboration with the community. Develop and optimize KV cache offloading frameworks for LLM workloads, supporting multi-level cache offloading and reuse across CPU, SSD, and remote storage to improve inference efficiency. (Team project: FlexKV) Drive R&D on compute performance in distributed training, and explore methods and technologies for performance optimization. Study computational challenges in machine learning systems, identify common needs and bottlenecks, and build example code, acceleration libraries, or frameworks accordingly. What We Need to See: Over 5 years working experience in the technology industry, with master’s degree or above in computer science, mathematics, electrical engineering, automation, or related fields. Strong interest in accelerated computing, parallel computing, and heterogeneous computing, with the motivation to explore these areas in depth. Solid programming skills, with a good understanding of data structures and computer systems fundamentals. Strong learning agil

NVIDIA is seeking a creative and analytical Capacity Planner to join our Operations team and drive the scaling of our Boards & Systems manufacturing across all business units. In this cross-functional role, you will lead the weekly planning cycle, collaborate with Operations, Manufacturing, Supply Chain, Engineering, Finance, and Business Units, and leverage advanced analytical models to resolve capacity constraints, rationalize capital investments, and drive execution strategies for senior management. What You'll Be Doing Run the weekly capacity planning cycle for Boards & Systems, including forecast ingestion, supply planning alignment, Contract Manufacturer (CM) and testing reviews, and preparation of planning outputs. Consolidate and validate core planning inputs (18-month forecasts, NPI consumption, SKU mappings, CM commits, yield data) across enterprise applications like Anaplan. Analyze required versus available capacity, identify bottlenecks, and perform scenario analysis using data models to drive risk mitigation strategies. Lead capital investment, decisions based on capacity requirements, rationalize forecast changes, and optimize volume loading across CMs to meet target supply and revenue goals. Coordinate workflows across Supply Planning, Business Units, Contract Manufacturers, Production Planning, Purchasing, Manufacturing/Test Engineering, Finance, and NPI in a multi-program platform environment. Partner with IT teams to integrate planning models with enterprise systems, establishing standardized workflows, data pipelines, and toolsets. Present clear, data-driven execution plans, operational risk insights, and mitigation strategies to senior management. Align with cross-regional teams (US, Israel, APAC) to maintain seamless operational execution and standardized planning frameworks. What We Need to See 5+ years

NVIDIA is seeking a Senior Staff SRE to build and operate reliable, scalable compute platforms that support global engineering workloads. This role spans Kubernetes, KubeVirt, bare-metal infrastructure, automation, observability, and AI-enabled operations. Join a team that solves complex infrastructure challenges, builds durable automation, and improves the reliability and operational experience of critical compute services. What you’ll be doing: Build, operate, and improve large-scale Kubernetes, KubeVirt, Linux, container, and bare-metal compute platforms, with a focus on performance, capacity, reliability, and operational scale. Lead bare-metal provisioning and lifecycle management in data centers, including PXE boot, DHCP, DNS, OS provisioning, hardware validation, and fleet automation. Develop automation, self-service capabilities, and observability solutions using APIs, Python or Go, Infrastructure as Code, configuration management, metrics, logs, traces, and service-health data. Define and operate SLOs, SLIs, error budgets, alerting, and incident-response practices; lead complex incident investigations, corrective actions, and blameless postmortems. Partner with infrastructure, security, hardware, data-center, and application teams to deliver global platform initiatives, and participate in an on-call rotation. What we need to see: BS in Computer Science, Engineering, a related technical field, or equivalent experience, plus 10&#43; years operating production infrastructure or platform services. Strong expertise in Kubernetes administration, KubeVirt, Docker, containerization, microservices, Linux systems, and resolving distributed-system challenges. <l

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Senior Process Analysis Engineer As a Senior Process Analysis Engineer in Micron’s Automation Development group at Taiwan Taichung, you will play a critical role within the Process and Process Integration team to enhance inline defense line effectiveness, improve process control capability, and prevent yield-related excursions through data-driven and AI-enabled solutions. You will take ownership of issue investigation, root cause analysis, Design of Experiments (DOE), and Continuous Improvement Programs (CIP) for critical materials and manufacturing processes. In addition, you will collaborate with cross-functional teams to integrate advanced process control methodologies, AI-assisted analytics, and digital solutions into process flows supporting next-generation high-density memory products. Job Responsibilities Leverage AI-assisted and AI-enabled technologies to improve manufacturing intelligence and decision-making, including applications in Statistical Process Control (SPC), Fault Detection and Classification (FDC), Automated Defect Classification (ADC), Internet of Things (IoT), and Data Analytics (DA). Apply AI-supported analytical approaches to identify process variations, improve inline defense line effectiveness, and accelerate root cause investigation and yield learning. Collaborate with internal and external partners, including Process Engineering, Failure Analysis, Quality, and Manufacturing teams, to correlate Defense Line (DL) signa

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. You will: Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the modern

About BlockTech BlockTech is an algorithmic trading firm operating at the frontier of global crypto derivatives and spot markets. We trade 24/7 across some of the fastest-moving, most data-rich venues in finance. Crypto remains one of the few markets where a researcher can still meaningfully move the edge: abundant data, novel microstructure, and the shortest possible loop between a research idea and live PnL. We're looking for an experienced Quantitative Researcher to take ownership of that edge and push it further. The role This is a senior, hands-on research seat on our trading floor. You'll own a research agenda end-to-end from hypothesis, dataset construction, feature engineering, model training, backtesting, live deployment, monitoring, and iteration. You'll be trusted to set its direction. You'll work shoulder-to-shoulder with fellow researchers, traders and analysts, shape how we price and trade, and help raise the bar for research across the floor, including mentoring less experienced researchers and influencing the tools and standards the team relies on. What you'll do Own price-prediction, signal, execution, and anomaly-detection models across crypto derivatives and spot markets from idea to live PnL using state-of-the-art ML Shape our research, backtesting, and trading infrastructure together with engineers, so good ideas reach production quickly and safely Own models in production: monitor live performance, diagnose decay, and iterate on what you ship Set research direction alongside traders, deciding which trades are worth making and why Raise the research bar by mentoring colleagues, reviewing work, and setting standards for rigour What we're looking for 4+ years of hands-on quantitative research and/or applied ML experience, with a track record of models you've taken into production trading live A strong academic foundation in a quantitative discipline (mathematics, physics, statistics, computer science, ML/AI, or similar) Fluency in Python and the m

Sr. Software Engineer The Team + The Role Pendo's engineering teams build the product experiences that help customers understand, improve, and act on product usage data. This team is focused on AI-powered features that turn raw usage signals into automatic, actionable suggestions, reducing the manual work customers need to do before they can get value from Pendo. As a Senior Software Engineer, you will help shape and ship intelligent product experiences from discovery through delivery. You will work full-stack with a lean toward frontend, using TypeScript, Vue.js, backend services, and AI coding tools to build high-quality features on a small, fast-moving team. This role also owns product judgment: validating problems with customers, sizing opportunities, defining success metrics, and making pragmatic tradeoffs in ambiguous spaces. This role is based in our Sheffield office. What this looks like day-to-day AI-powered feature delivery: Build and ship features that use AI to turn product usage data into actionable suggestions for customers. You will work end to end across the experience, with attention to quality, usability, and the unique failure modes of AI-backed products. Full-stack engineering: Own delivery across the frontend and backend, with a strong lean toward TypeScript, Vue.js, DOM-level work, component architecture, and in-browser data capture. You will reason about backend services and APIs while building polished, reliable customer-facing experiences. Product discovery: Help validate problems, shape scope, and test direction before and while building. You will join customer calls, test prototypes, and use real feedback to make sure the team is solving meaningful problems. Success metrics and iteration: Define what success looks like for the features you build and use product usage data to guide iteration. You will not just close tickets; you will measure whether the work is creating the intended customer impact. AI-enabled development: Use AI coding too

Datadog’s Cloud Observability group is one of the core data retrieval and processing groups powering our foundational product, Infrastructure Monitoring. The group’s scope includes integration with all major hyperscalers (AWS, Azure, GCP, OCI), as well as both regional and GPU-specific cloud providers. As Director, you will own engineering for all clouds, generating more than 10 million metric points per second, managing ~40 engineers through a team of Engineering Managers. You’ll partner with Senior Directors and product leadership to shape the roadmap, not just execute against it, managing the growth of one of Datadog’s foundational teams. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You'll Do: Own engineering for all of Cloud Observability Manage ~40 engineers through a layer of Engineering Managers; this is a manager-of-managers role Shape the roadmap alongside product leadership rather than simply executing against it — push back on, iterate on, and help author the strategy for your area Drive AI adoption across the engineering org, from tooling and workflows to product features and team practices Navigate cross-team dependencies across the Agent, Telemetry Onboarding, Integrations, Action Platform, and Infrastructure Monitoring. Build and retain engineering talent in NYC, Boston, and Paris, mentor Engineering Managers toward Director readiness, and participate in the on-call rotation Who You Are: You have directly managed Engineering Managers, not just individual contributors You have deep experience with one or more cloud providers, ideally with experience operating large-scale systems in the cloud. You have a solid understanding of cloud economics, as well as how to balance performance and cos

The Applied AI team designs and builds algorithmically driven features in the Datadog app. We work across a range of applications, primarily focusing on analysis on streaming data such as anomaly detection , error outliers and faulty deployment analysis . As an Applied Scientist you will work on building models and algorithms for machine learning powered features within the Datadog platform. You will work closely with our engineering and product partners to explore, build, scale and deliver these features that we incubate within the Applied AI team. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design solutions for our different use cases. You will research and benchmark relevant algorithms to find the best fit for our use-cases Leverage machine learning algorithms and statistical techniques to build new scalable product features Develop, deploy and monitor new and existing features to production Participate in our journal club by reading and presenting the latest academic research papers to the team Explore, analyze and tell the story behind high volumes of data flowing through Datadog systems Maintain and monitor the models, services and infrastructure owned by your team Participate in your team’s on-call rotation Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering, Machine Learning or related scientific field or equivalent experience You have experience working with high-scale systems and datasets including building models, applying machine learning to real business problems, and writing production data pipelines You can explain complex ideas and algorithms to non-technical audiences You care about code simplicity and performance You are excited to work on

Senior Product Manager, Cluster Scalability Location: Dublin About the Role MongoDB is hiring a Senior Product Manager to own scalability for the Atlas data platform. Atlas is how the world’s most demanding applications run on MongoDB — from real-time gaming and financial transactions to AI workloads with unpredictable traffic patterns. When those applications grow, slow down, spike, or contract, scalability is the layer that decides whether the customer trusts us to keep running their business. This role owns the end-to-end product experience for how customers scale up, scale down, and horizontally scale their Atlas deployments. That includes vertical scaling (instance tier changes), autoscaling, horizontal scaling (sharding and shard key strategy), and the operational workflows around all of them. You will set the strategy, drive execution with engineering, and be accountable for measurable year-over-year improvements in how reliably and predictably customers scale. We care less about whether you’ve worked on databases before and more about whether you’re the kind of PM who can ramp fast on a hard technical domain, form a clear opinion about what needs to happen, and defend that opinion to senior engineers, field partners, and enterprise CTOs, especially when they disagree with you. Database and scaling concepts are teachable. Judgment, conviction, and crispness are not. Responsibilities Set a clear, opinionated vision and strategy for Atlas cluster scalability and translate it into concrete, prioritized bets each release. Own the end-to-end roadmap for vertical scaling, autoscaling, and horizontal scaling, including the operational and observability surfaces customers rely on during scaling events. Make hard prioritization calls, including saying no to things with real customer or leadership support, and own those decisions and their consequences. Build deep technical understandin

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. Lyft Infrastructure builds the systems engineers depend on to ship stable, scalable, and efficient services. We're hiring a Senior Technical Program Manager to run cross-functional programs across our infrastructure and data platform teams. This role blends program delivery with product sense: you'll own the roadmap for your area, set priorities, and act as the voice of the customer back into how we build. Responsibilities Run infrastructure programs end to end, from kickoff through delivery Own the roadmap for your platform area: shape the strategy, sequence the work, and make the prioritization calls Drive data platform migration and modernization work, coordinating across engineering, data, and platform teams to keep dependencies and timelines under control Be the voice of the customer: partner with engineering teams across Lyft, surface their pain points, and feed that back into priorities and roadmaps Define success metrics and adoption goals, gather and document customer requirements, and make sure what ships actually solves the problem Build feedback loops with customer teams and turn what you hear into concrete improvements Partner with engineering and infrastructure leads to build plans, call out risks early, and keep stakeholders aligned Own program health: track milestones, surface blockers before they slip, and keep decision-makers in the loop Use your technical background in distributed systems and data infrastructure to ask sharp questions and build plans the team believes in Share in the team's release oncall rotation Experience 5+ years in Technical Program Management or a TPM/PM hybrid role A background in software, data, or systems engineering, enough to go deep with engineers Experience owning a roadmap: setting strategy, prioritizing across competing demands, and defining what suc

Our Purpose Mastercard powers economies and empowers people in 200&#43; countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Analyst, Analytics & Metrics - Open Finance Overview The Strategic Customer Analytics - Open Finance team serves as a trusted analytics partner to Mastercard's Open Finance clients, helping customers understand performance, identify growth opportunities, and maximize value from Mastercard's data and connectivity solutions. The Senior Analyst, Analytics & Metrics will play a critical role in transforming complex datasets into actionable insights that drive business decisions for both internal and external stakeholders. This role combines advanced analytics, data storytelling, client consulting, and cross-functional collaboration. The successful candidate will partner closely with Customer Success, Product, Engineering, Business Intelligence, and executive leadership teams to develop performance reporting, investigate trends, uncover opportunities, and communicate findings through compelling analyses and presentations. The ideal candidate is highly comfortable working with large datasets, and capable of translating technical concepts into clear business recommendations. They will have opportunities to influence strategic initiatives, support key client relationships, and help shape the future of analytics within Mastercard's Open Finance organization. You will also collaborate closely with