Data Analytics Engineer Jobs

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain

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 Every AI insight, every experiment, every cohort at Amplitude starts with a query. Our in-house OLAP engine, Nova , processes trillions of events in real time — turning raw behavioral data into fast, trustworthy answers that power decisions for thousands of product teams worldwide. We're entering a world where AI agents don't just assist product teams — they ship features, run experiments, and make prioritization calls autonomously. What makes that possible is agents' ability to verify their work against real product data continuously. That makes Nova the critical infrastructure in the loop, and as non-stop agents become the main source of queries, the demand on Nova's throughput, correctness, and operational rigor grows dramatically. We're looking for a Senior Software Engineer who wants to go deep on the engine internals and the

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 Every AI insight, every experiment, every cohort at Amplitude starts with a query. Our in-house OLAP engine, Nova , processes trillions of events in real time — turning raw behavioral data into fast, trustworthy answers that power decisions for thousands of product teams worldwide. We’re entering a world where AI agents don’t just assist product teams — they ship features, run experiments, and make prioritization calls autonomously. What makes that possible is agents’ ability to verify their work against real product data continuously. That makes Nova the critical infrastructure in the loop, and as non-stop agents become the main source of queries, the demand on Nova’s throughput, correctness, and operational rigor grows dramatically. We’re looking for a Staff Software Engineer who wants to go deep on both the engine internals and

As Senior Data Scientist for Engineering Systems you will work independently alongside sharp, generous, and pragmatic engineers from Server Query, Atlas Clusters, and Release Quality, among other teams. Together, we tackle problems spanning resource scaling across the Atlas fleet, safe feature rollout to MongoDB clusters, automated incident response and query engine performance. Join the Platform Data Science team and help us research, prototype and ship machine learning features for MongoDB’s core server, query engine and Atlas, our database-as-a-service cloud offering. We are looking to speak to candidates who are based in Dublin or Cork for our hybrid working model. What You'll Do Partner with Server Query, Atlas Clusters, Release Quality and other engineers to embed algorithmic rigor and optimization into resource scaling, release-safety and monitoring systems across the fleet and inside query engine Deliver production-ready, thoroughly tested statistical and ML algorithms with well-identified limitations that deliver measurable business impact, not just an impressive-sounding methodology Own the full feedback loop: instrument model architecture with the metrics needed to track performance and create dashboards in collaboration with our stellar analytics team, collect feedback from users and metrics to diagnose issues or opportunities, and iterate accordingly Deliver thoughtful, kind code reviews to your peers and act as a core contributor to internal packages, tooling, and team processes that increase developer productivity Measures of Success In 3 months, you’re familiar with our workflow, have an elementary understanding of our product and what teams we work with. You have delivered small-to-medium improvements to our project portfolio In 6 months, you’ve delivered one feature you researched and prototyped from scratch and demonstrated its impact on business metrics of your choice In 12 months, you've established a track record of shipping ML-driven improveme

The Data Science & Analytics team at Asana is how the company turns data into decisions — defining the questions that matter, surfacing the answers, and making sure insight is at the center of every critical product and business call. As a Senior Analytical Engineer, you sit at the intersection of Data Engineering, Analytics, and Data Science, and you own the data foundations for a business domain end to end. Your mandate is to turn raw data into reliable, business-ready datasets that PMs, analysts, data scientists, and leaders actually trust and use — and to define the business logic and metric standards that make AI-powered self-serve trustworthy. You consume governed Silver tables and produce the Gold layer and semantic layer beneath Asana's most important metrics, dashboards, and Genie spaces. This role is based in our Warsaw office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday, with the option to work from home on Wednesdays and, depending on the work and the teams you partner with, on Fridays. If you're interviewing for this role, your recruiter will share more about the in-office expectations. What you'll achieve: Own the Gold layer for a given business domain (e.g. PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on. Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good. Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie. Own the metric dictionary for your domain: a single source of truth for what each metric means, who owns it, a

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Team The Proactive Insights team is a newly formed team at the center of Mixpanel's AI-first analytics vision. With a greenfield charter, we're building the intelligent layer that transforms Mixpanel from a tool you query into a partner that works for you. We answer the question every data-driven team asks: "What changed, why, and what should I do about it?" We proactively keep users informed about what matters in their data, delivering the right insights and recommendations at the right time, to the right places, both inside and outside of Mixpanel. Some examples of what we are building: Signals : Statistical analysis that automatically identifies which user behaviors cause downstream business outcomes — such as which actions genuinely improve 30-day retention — using causal inference to move beyond correlation Forecasting : Time-series modeling that projects whether a KPI (e.g. Signups) will hit its goal by end of quarter — including trend decomposition, seasonality adjustment, and confidence bands against a target. Simulation : Causal impact modeling that estimates how moving one metric (e.g. weekly sharing rate) by a given amount will ripple through to downstream KPIs like retention or revenue — giving teams a quantified basis for prioritization Cohort Detection : Automated identification of at-risk user cohorts by finding active users who resemble known churned segments across both behavioral patterns and descriptive characteristics, before they churn. Offline batch survival analysis models that estimate each user's probability of a future outcome (e.g. likelihood to churn or convert withi

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value . Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling . As an Analytical Engineering Manager, you lead a team of Analytical Engineers who own the data foundations for the business: the Gold layer, canonical metrics, certified dashboards, and semantic layer that make Asana's most important numbers trustworthy, and that make AI-powered self-serve through Claude and Databricks Genie actually work. You sit at the intersection of Data Engineering, Analytics, and Data Science, and you are accountable for whether business stakeholders trust the data in your team's domains and can answer their own questi ons without routing through your team. This role is based in our Warsaw office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . We offer a Contract of Employment (UoP) for our employees in Poland. What you’ll achieve Lead, grow, and develop a team of Analytical Engineers: Own hiring, coaching, performance, and career growth, setting a high bar for data-model quality and stakeholder trust. Own the Gold layer and semantic-layer strategy across your team's domains (e.g. PLG, marketing, revenue, NPI/AWM), taking accountability for curated data models, canonical metrics, dashboards, and Genie spaces. Treat every recurring insight as a product with an owner, a cadence, and an SLA, building a catalog of trusted, versioned data products instead of one-off rebuilds. Drive self-serve enablement by prioritizing Go

Join Delphi - Where Innovation meets transformation At Delphi, we believe in creating an environment where our people thrive. Our hybrid work model empowers you to choose where you work—whether it's from the office, your home, or a mix of both—so you can prioritize what matters most. We are committed to supporting your personal goals, family, and overall well-being while driving transformative results for our clients. We welcome exceptional talent from anywhere across the globe. Interviews and onboarding are conducted virtually, reflecting our digital-first mindset. Rooted in the region, we specialize in delivering tailored, impactful solutions in Data, Advanced Analytics and AI, Infrastructure, Cloud Security, and Application Modernization. Whether it’s enabling predictive analytics , transforming operations with automation, or driving customer engagement with intelligent platforms, we are the trusted partner for organizations ready to embrace a smarter, more efficient future. We are looking for a highly skilled and detail-oriented Consultant – Quality Assurance to ensure the delivery of high-quality, secure, and reliable software solutions. The ideal candidate will have strong expertise in test strategy, automation frameworks, security testing, and AI-driven QA practices. This role requires close collaboration with cross-functional teams to drive quality across the SDLC while implementing modern automation and security standards. What You’ll Do: • Design, develop, and execute comprehensive test strategies, test plans, and test cases • Perform functional, regression, integration, system, and UAT testing • Lead and implement test automation frameworks to improve efficiency and coverage • Conduct Vulnerability Assessment & Penetration Testing (VAPT) – Expert Level (Preferred) to identify security risks • Integrate AI/ML-driven testing solutions for pre

Join Delphi - Where Innovation meets transformation At Delphi, we believe in creating an environment where our people thrive. Our hybrid work model empowers you to choose where you work—whether it's from the office, your home, or a mix of both—so you can prioritize what matters most. We are committed to supporting your personal goals, family, and overall well-being while driving transformative results for our clients. We welcome exceptional talent from anywhere across the globe. Interviews and onboarding are conducted virtually, reflecting our digital-first mindset. Rooted in the region, we specialize in delivering tailored, impactful solutions in Data, Advanced Analytics and AI, Infrastructure, Cloud Security, and Application Modernization. Whether it’s enabling predictive analytics , transforming operations with automation, or driving customer engagement with intelligent platforms, we are the trusted partner for organizations ready to embrace a smarter, more efficient future. We are looking for a hands-on Senior QA Consultant to lead end-to-end testing of AI and Generative AI applications across enterprise environments. This role combines strong expertise in traditional QA engineering with modern AI evaluation and validation practices. The ideal candidate will drive quality assurance initiatives for RAG pipelines, multi-agent systems, OCR and Speech-to-Text solutions while ensuring production grade quality outcomes in regulated industries such as Finance, Healthcare, and Insurance. The successful candidate will lead a small QA pod, collaborate closely with engineering, AI/ML, product, and business teams, and act as the client-facing QA owner for enterprise AI engagements. This role requires strong technical leadership, automation expertise, AI evaluation capabilities, and excellent stakeholder management skills. Experience Requirements • 7–10 years of experien

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! The Role As a Senior Solutions Engineer, you will play a critical role at the intersection of data, technology, and customer impact. You will lead the design and delivery of scalable, reliable, and high-impact technical implementations for our enterprise clients. Working with diverse and complex datasets across industries, you’ll build and optimize end-to-end analytics solutions that directly influence how customers engage with the Forma platform. You’ll partner cross-functionally to identify opportunities, scope high-value solutions, and deliver outcomes that drive measurable business impact. This is a highly visible, client-facing role that combines hands-on technical expertise with strategic thinking. What You’ll Do Lead strategic technical engagements with enterprise clients, guiding solution design for complex business challenges using the Forma platform Design, build, and optimize scalable data architectures, pipelines, and workflows (e.g., PySpark, Databricks) Translate business requirements into robust, production-ready data solutions Design and deliver custom code and customer-specific integrations to extend the Forma platform for unique client requirements Partner with Professional Services to extract, transform, and analyze client data to optimize incentive compensation and sales performance strategies Collaborate with Product, Engineering, and Customer Success to deliver high-quality, actionable datasets and insights Drive improvements in data infrastructure, perfor

Key Responsibilities Enterprise Data Strategy & Client Engagement: Develop and maintain a comprehensive data architecture strategy that aligns with organizational and client business objectives. Serve as a key technical advisor for clients, translating business requirements into innovative data solutions. Build and maintain strong client relationships by providing expert guidance and managing expectations throughout project lifecycles. Data Modeling, Design & Engineering: Design and optimize both logical and physical data models to support enterprise-wide systems. Architect data warehousing solutions, overseeing the integration of data from multiple sources to enable robust business intelligence and analytics. Directly develop, test, and implement ETL processes and data pipelines, ensuring data quality, consistency, and performance. Technology Evaluation & Implementation: Evaluate emerging data technologies and tools to determine their fit within the existing architecture and potential for future scalability. Oversee the integration of new technologies into the enterprise data architecture, balancing innovation with risk management. Team Leadership & Hands-On Management: Lead cross-functional teams, providing mentorship and technical guidance to junior data engineers and architects. Maintain a hands-on approach by actively participating in coding, design sessions, and troubleshooting complex data issues. Ensure project milestones are met through effective resource management and team coordination. Performance, Security & Best Practices: Optimize data storage, retrieval, and processing performance across various systems. Collaborate with security teams to enforce data governance, compliance, and privacy standards. Establish and promote best practices in data management, data engineering, and architecture design. Documentation & Reporting: Develop and maintain comprehensive documentation covering data architecture designs, data flows, integrati

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus

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