Senior Ai Data And Analytics Engineer Jobs

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here). Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started. Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit. AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it. ------------------------------------------------------------------------------------------------------ ➡️ Mission: Join us as Analytics Engineer – Data Governance and become the architect of Qonto's data trust layer as we make our transition to a fully licensed bank. You will own end-to-end the Data Governance framework — defining rules, implementing controls, monitoring quality, and driving remediation across the company — so that every compliance report is reliable and every business decision is grounded in trusted data. You will work closely with Alice Fresko, our Head of Analytics Engineer, and with Paul, our Staff Analytics Engineer, and sit at the intersection of Data, Product, Engineering, and Compliance. This is a first-of-its-kind role at Qonto: you won't inherit a mature process, you'll build it. ➡️ As an Analytics Engineer at Qonto, you will: Build

Omada Health is on a mission to bend the curve of chronic disease. Job overview: We are seeking a Senior Software Engineer to help design, build, and scale modern data platform capabilities using cloud-native technologies and AI-driven solutions. In this role, you will develop reusable frameworks, platform services, and engineering patterns that enable teams to build reliable, scalable data-products and AI-powered workflows. You will also leverage Generative AI to enhance data discovery, governance, developer productivity, and self-service access to trusted data. Working closely with cross-functional teams, you will help shape a modern data platform that accelerates innovation while ensuring security, reliability, and operational excellence. Your Impact: Design, build, and operate scalable Data & AI platform capabilities for analytics, data science, and Generative AI use cases with strong practices around data quality, lineage, observability, security, and governance. Develop reusable abstractions, templates, services, and workflows that standardize how teams build and manage data pipelines and data products. Partner with Analytics, Applied-AI, Data-engineering and application teams to deliver platform capabilities that support business and clinical decision-making Evaluate and integrate modern data and AI technologies with a focus on scalability, reliability, developer experience, and cost efficiency Apply Generative AI technologies to improve data enablement, documentation, discovery, workflow automation, and platform usability Promote software engineering best practices, including clean code, automated testing, CI/CD, infrastructure-as-code, monitoring, and secure data handling About you: 5+ years of professional software engineering or data engineering experience building scalable data platforms, services, pipelines, or analytics infrastructure Hands-on experience with modern data architectures, including data lakes, lakehouses, warehouses, analytical datast

GAQ426R192 About the Role As Senior Manager, Finance Data and AI, you will lead the team that owns the data foundations, finance semantic layer, financial reporting, and AI-enabled analytics that power Databricks' Finance and Accounting organization. You will report to the Senior Director, Finance Data, AI & Strategy, and serve as the domain and technical anchor for a team that turns financial operations into trusted, well-governed data and reporting. This individual is expected to be based in Bengaluru. This is a high-impact role at the intersection of finance and accounting domain expertise and modern BI/analytics capability. It is less about deep distributed-systems engineering, and more about deeply understanding how Finance and Accounting operate (close, reconciliations, revenue recognition, chart of accounts) and building a trusted data foundations on top of the Databricks platform and Finance DataLake that Finance and Accounting can rely on every day. What You Will Do: Orchestrate jobs using Databricks Jobs and Lakeflow Declarative Pipelines, with built-in data validation and reconciliations, to ensure Finance and Accounting can trust the data behind every report Own and evolve the Finance semantic layer: metric definitions, business logic, and data models that ensure a single source of truth for financial reporting across Finance, Accounting, and the broader business Partner closely with Accounting during month-end and quarter-end close, providing hands-on support to ensure reporting data is accurate, timely, and reconciled, and driving timely resolution of data-related issues Build and maintain dashboards and reporting for monthly, quarterly, and executive-level reporting, translating financial data into decision-ready insight for Finance leadership and the CFO organization Identify, scope, and deliver AI use cases that materially change how Finance and Accounting work day to day, including forecasting automation, anomaly detection, and natural language

AI Fullstack Engineer Poland ABOUT US Capco is seeking experienced and motivated AI Engineers to help design, build, and deploy AI-enabled solutions for clients in the financial services industry. As part of this engagement, you will work on complex business, technology, and data challenges, applying modern AI engineering practices to create scalable, reliable, and production-ready solutions. We are seeking professionals combines strong software engineering skills with practical experience in large language models, machine learning, data platforms, and modern AI application development. You will collaborate with client stakeholders, product teams, data specialists, and engineers to turn business needs into AI capabilities that are explainable, maintainable, and aligned with enterprise standards. SCOPE OF SERVICES AI Solution Delivery Design, develop, test, and deploy AI-enabled applications and services. Build solutions using large language models, machine learning, retrieval-augmented generation, semantic search, and agentic AI patterns where appropriate. Translate client business problems into technical designs, implementation plans, and working software. Develop reusable AI components, APIs, prompts, workflows, and evaluation approaches. Ensure AI solutions are scalable, reliable, secure, and suitable for production use. Data, Knowledge, and Retrieval Engineering Work with structured and unstructured data sources to support AI-enabled discovery, reasoning, and decision support. Build or integrate search, retrieval, ranking, and knowledge management capabilities. Develop approaches that help AI systems understand business context, data assets, metadata, documentation, and other enterprise knowledge sources. Improve the quality, relevance, traceability, and explainability of AI-generated outputs. Collaborate with data engineering and platform teams to ensure AI solutions are well integrated with existing data ecosystems. Technical

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors The Analytics Engineering team at Nextdoor transforms diverse data sources into solutions for business challenges. As a lean yet impactful team, we cover the entirety of the Nextdoor business and excel in cross-functional collaboration to empower company-wide data-driven decision-making. By amplifying the voices of our platform's users, we play a pivotal role in building stronger, healthier communities. We’re at an exciting transition, evolving from a traditional Business Intelligence focus to a broader mandate that includes strengthening data foundations and developing data products, such as analytics self-serve, for all Nextdoor data consumers. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make As a Senior Analytics Engineering Manager , you will Develop and own the vision for Analytics Engineering, delivering curated datasets, dashboards, and

Senior Analytics Engineer 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 Vancouver 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 . 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,

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors The Analytics Engineering team at Nextdoor transforms diverse data sources into solutions for business challenges. As a lean yet impactful team, we cover the entirety of the Nextdoor business and excel in cross-functional collaboration to empower company-wide data-driven decision-making. By amplifying the voices of our platform's users, we play a pivotal role in building stronger, healthier communities. We’re at an exciting transition, evolving from a traditional Business Intelligence focus to a broader mandate that includes strengthening data foundations and developing data products, such as analytics self-serve, for all Nextdoor data consumers. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make As a Senior Analytics Engineering Manager , you will Develop and own the vision for Analytics Engineering, delivering curated datasets, dashboards, and

Senior Analytics Engineer 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 Vancouver 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 . 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,

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Senior Analytics Engineer As a Senior Analytics Engineer on the Platform team, you'll build the scalable data models and pipelines that power analytics, experimentation, and decision-making across Coinbase. Our Analytics Engineering team transforms raw data into trusted, well-modeled sources that stakeholders across Product, Engineering, and Data Science rely on daily. You'll own end-to-end data solutions for specific business domains, turning complex data flows into clean, reusable frameworks that unlock commercial value at scale. What you'll do: Own end-to-end data modeling for assigned business domains, from understanding source system data flows through designing modular, reusable models (star/snowflake schemas) that serve as the single source of truth for downstream teams. Build and optimize ETL/ELT pipelines using modern tools like dbt and Airflow, ensuring data quality, reliability, and performance at scale across Snowflake or similar warehouse architectures. Partner with Engineering, Product, and Data Science teams to identify data gaps, define requirements, and deliver data products that directly enable experimentation, ad hoc analysis, and business metric optimization. Develop scalable abstractions and frameworks (UDFs, Python packages, internal data apps) that multiply the efficiency of other data teams and reduce time-to-insight across the organization. D

Data & AI Strategy Consultant – Manager/Senior Manager Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent Craft bold strategies. Inspire data-driven transformation. Lead the AI future. The Role Join Capco's Data Strategy & Advisory team as a Manager or Senior Manager, shaping enterprise-level AI and data strategies for the world's leading financial institutions. This is a high-impact role for strategic thinkers passionate about the intersection of data, AI and business value. You will guide clients in envisioning and realising AI-driven competitive advantage—beyond tooling and beyond pipelines—while helping organisations adopt AI-enabled ways of working responsibly, balancing innovation with governance, human judgement and measurable business outcomes. What You'll Do Partner with C-suite clients to define strategic AI ambitions, aligning enterprise data and AI capabilities with business priorities, competitive differentiation and long-term value creation. Act as a subject matter expert on emerging AI and data technologies, advising clients on how to responsibly adopt innovations—including Generative AI, Agentic AI and intelligent automation—to accelerate business outcomes. Lead the definition of enterprise data and AI strategies, identifying high-value use cases and translating them into practical roadmaps that balance opportunity, risk, governance and organisational readiness. Facilitate executive workshops, visioning sessions and strategic decision-making, developing compelling board-level narratives and investment cases while using AI-enabled insights and approved AI tools to enhance analysis and strategic recommendations. Collaborate across Capco's Engineering, Architecture, Risk, Product, Innovation and Data teams to ensure strategic recommendations are actionable, commercially viable and aligned with responsible AI principles. Beyond client delivery, you will also: Contribute to Capco's perspective on how AI is reshaping

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . We're hiring an Analytics Engineer to join the GFCO Analytics Engineering team and build the data foundations that power customer experience and compliance operations at Coinbase. You'll own end-to-end data pipelines, develop trusted metrics, and enable CX stakeholders to make faster, better decisions with clean, reliable data. This is a high-impact role where you'll directly influence how we serve and protect our customers while scaling our analytics capabilities. What you'll do: Own the design, build, and maintenance of data models and pipelines that support CX operations, compliance reporting, and customer insights, ensuring data is accurate, timely, and well-documented. Partner with CX Operations, Compliance, and Product teams to translate business needs into data requirements and deliver self-serve analytics solutions that reduce manual effort. Build and maintain dashboards, metrics, and reporting tools that give CX leaders visibility into performance, customer trends, and compliance health. Drive data quality and governance within the CX data domain by implementing testing, monitoring, and documentation standards that ensure stakeholder trust in the data. Identify opportunities to automate recurring data workflows and reporting processes, shifting the team from reactive requests toward scalable, self-serve solutions. Collaborate with broader Data Engineering an

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE SHOULD YOU ACCEPT THIS CHALLENGE… The GTM BI team at Pure Storage supports Revenue Operations across pipeline, forecasting, seller performance, and executive reporting — and we are at an inflection point. We are midway through a strategic migration to dbt as our transformation standard. Beyond that, our roadmap includes scalable automation frameworks, semantic business intelligence, and AI-enabled workflows that help surface insights with less manual effort. As a Senior Analytics Engineer, you will help drive that journey end-to-end. This role is grounded in modernization first: building scalable dbt foundations, improving quality and engineering standards, and enabling the team to operate more efficiently before scaling broader AI-enabled capabilities. You will partner closely with BI analysts, Sales Operations, Systems teams, and backend engineering partners to modernize how analytics is engineered, governed, and consumed across the organization. This role is for someone who wants to build — not maintain. WHAT YOU’LL DO… Lead and contribute hands-on to the team’s dbt and Snowflake modernization initiatives Build scalable semantic and metrics layers supporting GTM domains including pipeline, forecasting, quota, attainment, and seller performance Design and maintain robust ELT/ETL pipelines, orchestration workflows, and reusable business-facing datasets Build CI/CD, testing, observability, lineage, and data qualit

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is The Role Platform Observability & Analytics runs the infrastructure that tells Elastic the truth about its own platform. The observability clusters show Cloud engineers how production is behaving right now, and the analytics pipelines show the business how the platform and the products get used over time. This role sits on the observability side. We run 200+ hosted deployments across every supported cloud region, ingesting logs, metrics and traces for all of Elastic Cloud, plus the SLA and SLO monitoring for ESS and Serverless. When Cloud engineering needs to know what production is doing, they're looking at something we run. What You Will Be Doing Owning end-to-end delivery of moderate-to-high complexity projects on the team’s roadmap , with minimal day-to-day direction. Operating and hardening shared Elastic Cloud infrastructure (ECH, ECE, and ECK) as Infrastructure as Code – writing and reviewing the Terraform, Python, and Go that other engineers depend on. Carrying a 24/7 on-call rotation: responding to incidents, driving them to resolution, and writing clear RCAs/postmortems that lead to lasting fixes rather than repeat pages. Reviewing others’ code and designs, and being a trusted second set of eyes on production changes to critical infrastructure. Mentoring less experienced engineers, and proactively raising risks, ideas

Why Harvey At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come. This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started. Role Overview We’re looking for a versatile Senior Analytics Engineer focusing on Product to architect event data models that power decision-making at Harvey. With product-market fit already proven and demand surging across diverse customer segments, you’ll design clean, reliable pipelines and semantic data models that turn raw events into usable insights. As an Analytics Engineer on our team, you’ll help evolve our data stack, champion best practices in testing and documentation, and collaborate closely with product, GTM, and leadership to ensure every team can answer its own questions with confidence. If you combine engineering rigor with a love of storytelling through data we’d love to meet you. What You'll Do Design and build scalable data models and pipelines using dbt to trans

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. Responsibilities Data Pipeline Engineering: Build scalable ingestion pipelines for structured, semi-structured, and engineering data sources. Workflow Orchestration: Develop reliable batch, scheduled, and event-driven workflows using Apache Airflow and cloud-native services. ETL / ELT Frameworks: Implement reusable pipeline patterns, transformations, incremental ingestion, and data quality checks. Schema Management: Implement schema registry, schema versioning, schema evolution, and compatibility controls. Delta Detection: Build change detection and incremental refresh mechanisms for efficient large-scale data synchronization. Entity Extraction: Extract and normalize key identifiers such as Lot, Die, Wafer, Test, Flow, Product, and Step. Cloud Landing Zones: Set up secure AWS, GCP, and on-prem landing targets for validation and analytics pipelines. <