Data Engineer Jobs

NVIDIA’s DGX Cloud organization is seeking a Senior Data Engineer to become part of its data team! We develop the reliable data foundation that supports fleet health, capacity, utilization, cost, reliability, and operational decision-making throughout DGX Cloud. Our platform supports engineering, operations, finance, and product teams managing and expanding large GPU fleets across cloud service providers and NVIDIA Cloud Partners. We are looking for a practical engineer and technical lead to take charge of a key part of the Navigator data platform. We develop the systems that transform distributed infrastructure telemetry and operational data into dependable, managed data products that support fleet health, capacity, utilization, cost, and operational decisions. We are seeking a hands-on, platform-minded engineer to build and evolve the systems that turn distributed infrastructure telemetry and operational data into reliable, governed data products. You will work across ingestion, transformation, data quality, platform architecture, security, observability, and self-service consumption to help make Navigator and the DGXC data platform a dependable source of truth. We do expect strong engineering fundamentals, experience operating production systems, and the ability to learn new platforms and domains quickly. What you'll be doing: Own systems end to end. For example, work from ambiguous customer and operational needs through architecture, implementation, deployment, observability, incident response, and ongoing support. Construct data pipelines and products. Such as designing and maintain batch and streaming ingestion, transformation, reconciliation, and serving paths for fleet, capacity, utilization, cost, scheduling, and operational telemetry. Build shared libraries, workflow and DAG or equivalent experience abstractions to evolve the data platform. Develop deployment tooling, data

We're looking for an ML Data & Platform Engineer to own the infrastructure that powers our speech AI models: the pipelines that source and prepare training data, and the platform that trains, evaluates, and serves them in production. Speech AI has a data problem most ML teams don't, and you'll be at the centre of solving it, working as part of our ML team to remove friction across the entire lifecycle and get better models into production faster. This is a broad, cross-functional role suited to someone who enjoys working across the full stack: data infrastructure, distributed systems, and production ML, and who takes ownership of problems end to end rather than waiting to be told what to fix. What you'll do Designing, building, and maintaining scalable data pipelines for ingesting, transforming, validating, and storing large datasets used to train our models Developing and maintaining web scraping and data acquisition solutions to keep training datasets fresh, high-quality, and available at scale Building and operating the infrastructure that lets the ML team deploy and evaluate new models quickly, and that serves models efficiently and reliably in production Optimising infrastructure for both iteration speed and production reliability, including GPU utilisation, job scheduling, and training efficiency Implementing observability (monitoring, logging, alerting) across data pipelines and ML systems to catch issues early and keep things running smoothly Troubleshooting complex issues across distributed systems, spanning data infrastructure, training, and inference Continuously improving our data and MLOps practices, and helping shape the roadmap for how our platform evolves as we scale What you'll need Strong proficiency in Python and SQL, with a solid backend or data engineering foundation Hands-on experience with containerisation and orchestration (Docker, Kubernetes), and working with a major cloud provider Experience building data pipelines and ETL/ELT processe

**English version below** Doit être local à Montréal Vous souhaitez travailler dans le domaine de la technologie au sein d'une banque d'investissement? Nous recherchons une personne pour rejoindre une équipe dynamique en tant qu’ Ingénieur(e) Data pour l’un de nos clients. Ce poste est destiné à un rôle d’ingénierie des données au sein de l’équipe MongoDB et Kafka . Nous sommes un groupe hautement technique qui réalise simultanément divers projets pour plusieurs secteurs d’activité. Les responsables métier et les experts sont répartis à l’échelle mondiale, ce qui rend de solides compétences en communication essentielles pour ce poste. Le ou la candidat(e) travaillera en étroite collaboration avec nos partenaires informatiques afin d’analyser les besoins métier et de mettre en œuvre les solutions répondant à ces exigences. À propos de mtrois : Depuis 2010, mtrois aide ses clients à résoudre leurs défis commerciaux et technologiques. Nous sommes une société de conseil en technologie et en affaires avec une main-d'œuvre mondiale qui réalise des projets commerciaux et informatiques significatifs dans certaines des plus grandes organisations de services financiers du monde. Services principaux Consulting et Conseil Services gérés Programme de diplômés Alumni Programme Alumni Pro Nous avons une présence mondiale et sommes experts dans la fourniture d'une qualité exceptionnelle à notre base de clients, offrant des services de conseil dans les domaines du risque, de la réglementation et de la conformité ; Produits des fournisseurs ; Support d'application ; Développement d'application ; Cyber et sécurité de l'information ; Science des données et DevOps. Notre programme Expert offre aux professionnels expérimentés l'accès à des rôles de premier plan dans la technologie, la finance, l'aviation et l'assurance. Rejoignez-nous pour travailler sur des projets technologiques révolutionnaires, des plateformes de trading internationales aux applications critiques pou

Join Truecaller – The place where innovation meets impact! Truecaller's mission is to build trust in communication by making it safer, smarter, and more efficient. Born in Sweden, trusted by the world, and here’s why we stand out: We are trusted by over 500 million active users every month across 190+ countries We identify over 15 billion calls daily, helping users avoid spam and scams We are powered by a team of 400+ employees from 45+ nationalities We always look for people who take initiative, own their work, and keep raising the bar. An entrepreneurial mindset matters here, especially when it turns bold ideas into real actions. We stay collaborative and focused, always searching for smarter paths forward. If you want to make an impact and grow with a team that inspires millions, you’ll fit right in. As an Engineering Manager, Data, you will lead a multidisciplinary team of ML engineers, data scientists, and data engineers driving some of Truecaller's most strategic initiatives. Your team will be responsible for advancing the trust graph, compounding intelligence, communication experiences, fraud detection, federated learning, calling, search, and the AI Assistant, technologies that sit at the core of Truecaller's strategy. This role combines deep technical leadership with people management: you will define the technical direction across an applied ML stack, foster the growth and well-being of a highly specialized team, and transform a research-driven roadmap into reliable, production-ready systems. What you'll do: Lead, grow, and retain a high-performing team of ML engineers, data scientists, and data engineers, investing deliberately in each person's development and career path. Set technical direction for the core intelligence behind Truecaller’s calling and search intelligence, along with the real-time serving and data platforms that support them. Own team planning, prioritization, and delivery, balancing near-term product commitments against long-term platfo

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management ro

Must be based in Vancouver The role We're hiring a dedicated data engineer to own the production data platform that our delivery, product, and engineering teams run on; designing integrated, governed data pipelines and delivering automated reporting, AI-assisted workflows, and predictive signals on top of them. You'll write production code, design systems, own CI/CD, and be accountable for the correctness of data that leaders make decisions on. What you'll do Design and operate our cloud data platform: ingestion, transformation, orchestration and serving. Integrate data from across the business (delivery tooling, CRM, product telemetry, finance, support and customer feedback systems) with shared identifiers, data contracts and lineage. Build automated and continuously refreshed reporting so teams manage by exception rather than chasing status. Connect approved AI agents to governed data with structured outputs, provenance, guardrails and human approval in the loop. Build feature pipelines and the MLOps controls behind predictive use cases: tests, versioning, promotion gates and drift monitoring. Own the engineering standards for data: testing, observability, environment promotion, PII classification and access control. What you'll bring Strong software engineering fundamentals: production-quality code, API and interface design, testing discipline, systems design. Real experience building and operating production data platforms on a cloud warehouse or lakehouse (Snowflake and AWS preferred) with dbt and a modern orchestrator. Practical AI tooling experience: something shipped, not prototyped. LLM-backed classification, extraction or structured-output pipelines; agent and tool-calling workflows; retrieval; evals. You can reaso

Role Overview Build reliable software services that power products, platforms, and business decisions. As a Senior Software Developer, you’ll design and deliver scalable applications, backend services, and integrations that perform well in production and evolve with changing business needs. You’ll apply strong software engineering practices across APIs, data-intensive applications, cloud services, AI-enabled solutions, and deployment pipelines. You’ll help shape technical solutions, improve system reliability, and contribute to a high-quality engineering culture. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Design and develop scalable backend services and applications using Python or TypeScript. Lead the development of APIs, integrations, reusable software components, and AI-enabled features. Build reliable solutions for data ingestion, manipulation, service-to-service communication, and intelligent automation. Apply AI technologies and modern software engineering practices to improve product capabilities, developer productivity, and operational efficiency. Make sound technical decisions around architecture, performance, security, scalability, and maintainability. Deploy and operate applications using AWS services and CI/CD practices while improving testing, monitoring, documentation, and delivery standards. These are the essentials you’ll need to get an interview 5+ years of professional experience developing and delivering production software. Strong hands-on experience with Python; TypeScript or similar languages is also valuable. Proven experience building backend services, APIs, integrations, and service-oriented applications. Experience applying AI technologies, such as generative AI, machine learning services, intelligent automation, or AI-enabled application features. Strong understanding of software design principles, testing, debugging, performance optimization, and secure development. Experience working with cloud platfor

InMobi Advertising is a global technology leader helping marketers win the moments that matter. Our advertising platform reaches over 2 billion people across 150+ countries and turns real-time context into business outcomes, delivering results grounded in privacy-first principles. Trusted by 30,000+ brands and leading publishers, InMobi is where intelligence, creativity, and accountability converge. By combining lock screens, apps, TVs, and the open web with AI and machine learning, we deliver receptive attention, precise personalization, and measurable impact. Through Glance AI, we are shaping AI Commerce, reimagining the future of e-commerce with inspiration-led discovery and shopping. Designed to seamlessly integrate into everyday consumer technology, Glance AI transforms every screen into a gateway for instant, personal, and joyful discovery. Spanning diverse categories such as fashion, beauty, travel, accessories, home décor, pets, and beyond, Glance AI delivers deeply personalized shopping experiences. With rich first-party data and unparalleled consumer access, it harnesses InMobi’s global scale, insights, and targeting capabilities to create high impact, performance driven shopping journeys for brands worldwide. Recognized as a Great Place to Work, and by MIT Technology Review, Fast Company’s Top 10 Innovators, and more, InMobi is a workplace where bold ideas create global impact. Backed by investors including SoftBank, Kleiner Perkins, and Sherpalo Ventures, InMobi has offices across San Mateo, New York, London, Singapore, Tokyo, Seoul, Jakarta, Bengaluru and beyond. At InMobi Advertising , you’ll have the opportunity to shape how billions of users connect with content, commerce, and brands worldwide. To learn more, visit www.inmobi.com Role Overview: We are hiring a Tech Lead / SDE IV to anchor and grow our Data Engineering capability within our Demand-Side Platform (DSP). This is a high-impact, technically hands-on leadership

About the Role & Team We’re looking for an Engineering Manager to lead the Data Infrastructure team within Statsig Experiment at Amplitude. You will lead a multidisciplinary team of software engineers, data engineers, and data scientists responsible for the systems that power experimentation at scale. The team owns three critical areas: Data ingestion: Collecting and importing experiment exposures, custom events, OpenTelemetry data, and real user monitoring data across SDKs, streaming systems, cloud storage, and customer data warehouses. Data computation: Building distributed computation systems that transform raw data into accurate, timely experiment results. Stats engine: Developing and productionizing the statistical methods that help customers make trustworthy decisions from their experiments. This is not a traditional data engineering management role. We are looking for a leader with a solid data science and statistical foundation who can connect advances in experimentation methodology with scalable production systems. You will help set our technical and scientific direction, translating new statistical methods and machine learning research into capabilities that customers can use reliably at scale. You’ll partner closely with data scientists, engineers, product managers, and customers to advance the state of experimentation. The ideal candidate is equally comfortable discussing causal inference and statistical power with data scientists, distributed computation architectures with engineers, and experimentation strategy with customers. What You’ll Do Lead and grow the team responsible for Statsig’s data ingestion, experiment computation, and stats engine. Define the technical and scientific strategy for advancing experimentation across both Statsig Cloud and warehouse-native deployments. Partner with data scientists and engineers to turn new statistical and causal inference methods into scalable, reliable product capabilities. Evolve our data and computatio

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. Who We Are: Shape the future of Roblox’s virtual economy. The Economy ML team is building the machine learning backbone that powers Roblox’s Marketplace, Developer Monetization, and Payments ecosystems. From intelligent pricing and personalized storefronts to dynamic layout optimization and avatar understanding, we’re reimagining how the Roblox economy drives user engagement, monetization, and creator success at scale. As a Principal Software Engineer (Data Systems) , you will architect, build and deploy high-scale, reliable real-time and batch data systems for personalization, search and recommendation across various product surfaces in Marketplace, Developer Monetization and Payments. You will be involved in key data projects from architecting event taxonomies and logging interfaces to real-time feature serving across multiple search and recommendation surfaces. What You’ll Do Act as data engineering lead for Economy ML, setting standards for batch vs streaming feature pipelines, table design, observability, and documentation used across the Economy group. Work as a hands-on contributor on our data systems to power content recommendation, search and personalization across Economy product

About the Team The Monetization Data Systems team builds the trusted data and product systems that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. About the Role We are looking for a Senior Software Engineer to design and build the next generation of our monetization data platform. You will own high-impact platform systems end to end, from architecture and implementation through testing, deployment, observability, and ongoing operation. This is a hands-on role for an engineer who enjoys solving ambiguous customer and business problems, designing durable systems, and partnering closely with Product, Data, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into reliable, scalable product experiences and platform capabilities. In this role, you will: Design, improve, and operate reliable, scalable backend services that power pricing, billing, ads, payments, entitlements, and other monetization platform capabilities. Own the architecture and implementation of critical workflows relevant to monetization data, data contracts, and integrations across product and business systems. Establish strong guarantees for correctness, availability, security, performance, reconciliation, and auditability across business-critical systems. Build reusable platform capabilities and developer tools that enable product teams to launch, measure, and iterate on monetization products

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

Work Flexibility: Onsite What You Get Out of the Internship At Stryker, we believe that developing the next generation of talent is just as important as developing life-changing medical technologies. As an intern, you won’t just observe — you’ll contribute to meaningful projects, gain exposure to leaders who will mentor you, and experience a culture of innovation and teamwork that is shaping the future of healthcare. As an intern, you will: · Apply classroom knowledge and gain experience in a fast-paced and growing industry setting · Implement new ideas, be constantly challenged, and develop your skills · Network with key/high-level stakeholders and leaders of the business · Be a part of an innovative team and culture · Experience documenting complex processes and presenting them in a clear format Who we want Challengers. People who seek out the hard projects and work to find just the right solutions. Teammates . Partners who listen to ideas, share thoughts and work together to move the business forward. Charismatic networkers. Relationship-savvy people who intentionally make connections with both internal partners and external contacts. <span style="co

Work Flexibility: Remote As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the future of enterprise data solutions. In this role, you will drive complex data initiatives, influence technical strategy, and partner with teams across the organization to build scalable, high-impact data products. This is an opportunity to solve challenging business problems while mentoring fellow engineers and elevating data engineering best practices. What You Will Do Lead the architecture, development, and modernization of scalable enterprise data platforms that support global procurement analytics and business transformation. Define and help execute a multi-year data engineering strategy focused on platform scalability, reliability, automation, technical debt reduction, and long-term maintainability. Design, build, and optimize Azure-based data solutions using technologies such as Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation. Integrate and harmonize data across multiple ERP systems by standardizing supplier, purchasing, and master data into common enterprise data models. Partner with procurement analysts, architects, engineers, and business stakeholders to translate complex business needs into reusable, scalable data products and engineering solutions. Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers to raise the overall technical capability of the team. Identify and implement AI-enabled approaches that accelerate development, improve data quality, automate documentation, support testing, and enhance analyst productivity. Evaluate and recommend tools, frameworks, patterns, and platform investments that improve performance, reliability, security, governance, and operational ef

Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: Notion’s Data Foundations team builds and operates the batch and streaming infrastructure behind our product features, analytics, search, and AI experiences. We’re looking for a hands-on technical leader to shape the next generation of this platform as Notion serves larger customers, expands globally, and supports more data-intensive products. You’ll identify the highest-leverage problems, set direction, build and develop a high-performing team, and lead multi-quarter initiatives across our data lake, streaming, distributed-compute, governance, and reliability systems. You’ll stay close to critical technical decisions while creating clear ownership, growing engineers and technical leaders, and helping the team execute as one—partnering closely with Data Engineering, Data Product, Search, AI, Infrastructure, and Security. This role can be based in either San Francisco or New York City. We work from our offices on Mondays, Tuesdays and Thursdays (our Anchor Days) because we do our best thinking and building together in person. We’re looking for someone who’s excited to work alongside the team during those days. What You