Senior Data Engineering Technical Lead Jobs

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 Networking division is a leading supplier of innovative end-to-end InfiniBand and Ethernet connectivity solutions and services for servers and storage. We offer market-leading solutions that include adapter cards, switches, cables, and software to support networking technologies. Our products optimize Data Center performance and deliver industry-leading bandwidth and scalability. In addition, we serve a wide range of sectors including high performance computing, enterprise, Data Center, cloud computing and Web 2.0. We are constantly reinventing ourselves to stay ahead of the market and bring groundbreaking products and services to the industry. Our product line is focused on delivering the most optimized Ethernet solutions for industries like Media and Entertainment as well as any other industry that can benefit from our DataStream and TCP/IP acceleration. What you will be doing: Drive multiple early-stage design concepts of Test Equipment & fixtures while working in fast-paced product development cycles. Independently lead Test Equipment & fixtures design from concept, through detailed design, and support it during Bring-up, Qualification and Mass-Production phases. Participate and lead design and design reviews of Test Equipment & fixtures by using our CMs (Contract Manufacturers) as the designers Collaborate in research of groundbreaking technologies, materials, and processes with other groups to bring in creative ideas that address evolving needs. What we need to see: B.Sc. in Mechanical Engineering or higher degree. 5+ years of experience in classical mechanical design of mechanisms, jigs, fixtures, products and machines development. Knowledge and experience in automation (pneumatics XYZ motion systems, etc) and in design of machining and sheet metal parts Knowledge and experience in static analysis and simulations.

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

About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale with trillions of data points per day, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams for tens of thousands of companies globally. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team The Datadog Security Libraries team owns the customer-side integrations behind our run-time security products App & API Protection , Workload Protection , and Code Security . Our libraries let customers automatically manage application security risk with continuous, real-time monitoring of vulnerabilities and threats against their web applications, serverless applications, and APIs, in production. Automatically integrated with Application Performance Monitoring (APM) distributed tracing and code-level context, our software empowers development, operations, and security teams to build and run secure applications. As a polyglot team we ship and maintain the security capabilities of Datadog's tracing libraries across .NET , Java , Go , Node.js , Python , Ruby , and PHP , on top of a shared C++ core and a set of HTTP proxy integrations (primarily Envoy, NGINX, and HAProxy). Our code runs inside thousands of production applications around the world. Recent work spans exploit prevention (RASP) and WAF detections, API Security, code security (IAST and SCA), and AI-assisted ("agentic") onboarding, always measured by real product outcomes and operational telemetry. The Opportunity We're looking for a senior, polyglot engineer to contribute across several of our security libraries, with .NET or Java expertise. You'll design and build security integrations and detection features, take them from prototype to production-hardened, and own them operationally as they instrument thousands of applications. As a se

About Datadog We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale with trillions of data points per day, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams for tens of thousands of companies globally. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Team The Datadog Security Libraries team owns the customer-side integrations behind our run-time security products App & API Protection , Workload Protection , and Code Security . Our libraries let customers automatically manage application security risk with continuous, real-time monitoring of vulnerabilities and threats against their web applications, serverless applications, and APIs, in production. Automatically integrated with Application Performance Monitoring (APM) distributed tracing and code-level context, our software empowers development, operations, and security teams to build and run secure applications. As a polyglot team we ship and maintain the security capabilities of Datadog's tracing libraries across .NET , Java , Go , Node.js , Python , Ruby , and PHP , on top of a shared C++ core and a set of HTTP proxy integrations (primarily Envoy, NGINX, and HAProxy). Our code runs inside thousands of production applications around the world. Recent work spans exploit prevention (RASP) and WAF detections, API Security, code security (IAST and SCA), and AI-assisted ("agentic") onboarding, always measured by real product outcomes and operational telemetry. The Opportunity We're looking for a senior, polyglot engineer to contribute across several of our security libraries, with .NET or Java expertise. You'll design and build security integrations and detection features, take them from prototype to production-hardened, and own them operationally as they instrument thousands of applications. As a se

About Datadog: We're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, and application tracing for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. You will: Solve a scaling bottleneck in a critical service Deploy a new feature to production, progressively rolling it out with feature flags Investigate and fix a production issue from a service your team owns Design a way to scale up a service for more traffic With your team, plan the most important projects to work on next Who You Are: You have significant experience in one or more languages You value code simplicity and performance You can design architecture to solve problems at high scale You have a BS/MS/PhD in a scientific field or equivalent experience You want to work in a fast, high-growth startup environment that respects its engineers and customers You have demonstrated ability to use AI coding tools in day-to-day workflows and build, validate, and refine AI-generated output in products You can design AI Backend systems, with awareness of quality, cost, and latency tradeoffs 6+ years of experience Bonus points: You've worked at high scale with systems like Redis, Cassandra, Kafka You wrote your own data pipelines once or twice before You have a strong background in statistics You have significant experience with Go, C, or Python You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all the above qualificat

We are building the best platform in the world for engineers to understand, scale, and protect their systems, applications, and teams. We operate at high scale—trillions of data points per day—providing always-on alerting, metrics visualization, logs, application tracing, and security insights for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way . 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: Solve a scaling bottleneck in a critical service Deploy a new feature to production, progressively rolling it out with feature flags Investigate and fix a production issue from a service your team owns Design a way to scale up a service for more traffic With your team, plan the most important projects to work on next Who You Are: You have significant experience in one or more languages You value code simplicity and performance You can design architecture to solve problems at high scale You have a BS/MS/PhD in a scientific field or equivalent experience You want to work in a fast, high-growth startup environment that respects its engineers and customers You’re excited about leveraging AI tools to enhance how you code, solve problems, and build – or eager to learn how You have demonstrated ability to use AI coding tools in day-to-day workflows and build, validate, and refine AI-generated output in products You can design AI Backend systems, with awareness of quality, cost, and latency tradeoffs Bonus: You’re motivated to push the boundaries of how AI can improve software engineering best practices and contribute to building AI-enabled products Datadog values people from all walks of life. We understand not everyone will meet all

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

AI frameworks like LangChain, LlamaIndex, and n8n are quickly becoming the default way developers build with AI — and MongoDB wants to be the data platform that shows up everywhere they build. As part of the AI Builders Experience (ABX) org, we're standing up a brand new engineering team in Gurugram to make that happen, and we're looking for Senior Software Engineers to be among its founding members. The team owns the connective layer between MongoDB and third-party AI frameworks, platforms, and tools — the integrations that let developers use MongoDB effectively with the AI stack they've already chosen. That means shipping into some of the fastest-moving open-source ecosystems in tech, working mostly in Python and TypeScript, and partnering with the Database Experience (DBX) org when an integration needs new driver, platform, or product capability underneath it. This is a self-sufficient team by design. You and your engineering manager will be based in Gurugram, and the group is set up to own its area end to end: to decide how integrations get built, tested, released, and maintained, without waiting on another time zone to unblock the day-to-day. You'll work closest with the engineers sitting next to you, pairing on hard problems, reviewing each other's code, and dividing up a broad portfolio, while collaborating with product, partners, field teams, and open source maintainers as the work requires. You'll integrate with fast-moving, often unproven technologies, make pragmatic calls in the face of ambiguity, and own high-visibility projects with minimal guidance. Priorities can shift week to week based on framework changes, customer demand, and partner needs, so we're looking for product-minded engineers who thrive on autonomy and take pride in shipping. Much of your work will happen in public: sending pull requests to upstream repositories, working through external maintainer review cycles, and representing MongoDB in developer communities. MongoDB engineering team

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview: We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space — including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale. The Logistics & ML group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high qu

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 Senior AI Security Engineer is responsible for defining, designing, and advancing enterprise-wide security strategies and architectures for AI, GenAI, and machine learning platforms. This role leads the development of secure AI systems at scale by embedding advanced security principles across the AI lifecycle and driving the adoption of standardized, security-by-design practices. The Senior AI Security Engineer partners with engineering, platform, and risk leadership to proactively address emerging AI threats, strengthen organizational security posture, and ensure resilient, compliant, and scalable AI deployments. This role operates with significant autonomy and influences security direction across multiple teams and domains.

Responsibilities Collaborate - Upholding CXD process, collaborating with product management and engineering to define and implement innovative solutions. Craft - Creating wireframes, storyboards, user flows, and process flows to effectively communicate interaction, design ideas and building application UI toolkits. Construct - Conceptualizing original ideas that bring simplicity and user friendliness to complex design roadblocks. Concentrate - Demonstrating attention to detail and problem-solving skills along with paying careful attention to staying on-brand. Convince - Presenting and articulating designs and key milestone deliverables to peers and executive level stakeholders. Minimum Qualifications A well-curated online and/or print portfolio/case study demonstrating UX/UI design skills, curiosity, positive attitude and strong drive to learn from a fast paced environment. Proven UX/UI design experience for multiple platforms including desktop, mobile, tablet. Excellent visual design skills with sensitivity to user-system interaction. Additionally experience in data informed and customer centric approach to design is key. Solid experience in creating wireframes, prototype, storyboards, user flows, and process flows. Proficiency in simplifying complex information through end-to-end experiences designs while co-creating with all the senior designers for smooth implementation. Up-to-date with the latest UI trends, tools, techniques, and technologies and their role in a commercial environment. 4-7 years of relevant experience with a B. DeS/M. DeS in Visual Design, Human-Computer Interaction, Interaction Design, or related is an advantage. General understanding of the front-end development process, including HTML and CSS. Ability to speak fluent English is a must. Demonstrable proficiency in presenting your designs and selling your solutions to various stakeholders through clear communication is key.

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange™️ platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 160+ public exchanges globally and thousands of private exchanges at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Senior Staff Rust Developer to join our Platform Convergence Team. This is a hybrid role based in San Jose, CA reporting to the Sr. Director, Software Engineering. Join us to build a new platform from the ground up that can scale hundreds of millions of users with high reliability and low latency. You will design and implement distributed system and core infrastructure components while collaborating closely with various stakeholders. What you’ll do (Role Expectations) Design and build a low-latency, high-throughput data forwarding plane using Rust, leveraging its async/await model for efficient I/O and service-oriented infrastructure Develop distributed, scalable systems with a focus on concurrency, fault tolerance, and messaging Implement and maintain gRPC-based APIs and services to integrate forwarding plane capabilities with control and orchestration layers Optimize system

AI only answers correctly when it can trust the data underneath it. This role owns two connected parts of how Sigma shows up in that world: where Sigma's experience lives outside its own product (MCP, a CLI, the Claude and ChatGPT marketplaces, integrations like Slack, Teams, and Glean), and the semantic layer that makes every one of those surfaces trustworthy. The first mandate is Sigma's AI ecosystem: defining Sigma's approach to MCP, giving external agents structured, governed access to Sigma's data model; owning the CLI, giving developers a fast way to work with Sigma outside the UI; and building Sigma's presence in the Claude and ChatGPT marketplaces, plus integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they already work. This is some of the most visible, fastest-growing surface area in the product. The second mandate is the semantic layer underneath it all. Every agent, chat answer, and integration is only as reliable as the data model behind it — get a metric definition wrong here, and every surface built on top inherits the mistake. This includes setting the roadmap for how semantic views connect across data platforms and how the model evolves as new AI capabilities emerge. What you'll do Define Sigma's approach to MCP, giving external agents and tools structured, governed access to Sigma's data model. Own the CLI roadmap, giving developers a fast, scriptable way to work with Sigma outside the UI. Build Sigma's presence in the Claude and ChatGPT marketplaces, along with integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they're already working. Set the roadmap for Sigma's data modeling strategy, including how semantic views connect across data platforms and how the semantic layer evolves as new AI capabilities emerge. Partner with engineering and design to ship integration and semantic modeling capabilities that hold up at enterprise scale.