Data Analytics Engineer (GenAI Application Team)

Data Analytics Engineer II (GenAI Application Teams)Role OverviewAs a Data Analytics Engineer, you will design and develop scalable analytical solutions that support GenAI application teams across search & discovery, AI companions/chatbots, customer support AI applications, and LLM evaluation workflows.This is a highly business-oriented role focused on bridging the gap between raw data and application-specific analytical needs. You will own data domains end-to-end, ensure data quality and usability, and transform complex datasets into actionable insights, monitoring systems, and evaluation frameworks.This is not a traditional Data Engineer role. The focus is on application logic, analytics, data modeling, quality, experimentation, and insight generation rather than infrastructure ownership or EL platform engineering.Important Hiring NotesLooking for candidates with a stronger analytics and product mindset than a traditional Data Engineering profile.Former Senior Data Engineers or Data Architects focused primarily on infrastructure and platform development are unlikely to be a strong fit.The role is not centered on building data infrastructure from scratch.Focus areas include deriving insights, defining meaningful metrics, solving business problems through data, and processing large datasets in a scalable manner.Ideal candidates have owned analytical domains end-to-end, including:

De verwachte ervaring van sollicitanten, evenals extra vaardigheden en kwalificaties die nodig zijn voor deze baan, worden hieronder opgesomd.
Data modelingData qualityExperimentation analysisDashboardingMonitoringStakeholder-facing analyticsTarget profile:
Approximately 2/3 analytics, product thinking, and business problem-solvingApproximately 1/3 data engineering and data modelingCandidates will be assessed on both technical data modeling skills and business orientation.ResponsibilitiesData Modeling & OwnershipOwn business and application data domains end-to-end.Ensure correctness, quality, and consistency of analytical datasets and logging.Design and maintain scalable analytical data models and reusable data products.Perform data governance responsibilities, including data classification, stewardship, quality monitoring, compliance, and security considerations.Maintain and improve data pipeline health through monitoring, troubleshooting, performance tuning, and proactive risk mitigation.Analytics, Monitoring & InsightsTransform large and complex datasets into actionable insights for operational, historical, and predictive analysis.Build reusable analytical datasets enabling self-service analytics across teams.Develop application-specific monitoring tables, quality dashboards, and cost dashboards.Analyze experiments, model behavior, and LLM evaluation results.Validate data and GenAI products through exploratory analysis and visualizations before release.Partner with product managers, scientists, and engineers to identify analytical opportunities and define analytics roadmaps.Qualifications & SkillsExperience & Mindset3+ years of experience in analytics, data, or software-adjacent roles working with large-scale data systems.Strong business orientation and customer-focused mindset.Ability to independently navigate ambiguity, prioritize based on impact, and drive initiatives end-to-end.Strong analytical thinking and ability to derive meaningful insights.Experience supporting production environments and delivering high-impact insights.Experience in ML/AI product environments, evaluation workflows, or model/error analysis is a strong plus.Resourceful and thoughtful use of AI tools and assistants.Technical SkillsStrong SQL skills and experience working with relational databases in analytical environments.Hands-on experience with Python and PySpark.Strong experience with data modeling and modern Data Warehouse practices.Experience building maintainable, reusable, production-grade analytical code and transformations.Experience working with free text, unstructured data, LLM-generated outputs, and AI application telemetry.Nice to have:
dbtSnowflakeStreamlitAirflowArgoNice to have: AI/LLM-related datasets and evaluation pipelines experience.Collaboration & CommunicationExcellent communication skills.Ability to explain technical concepts to non-technical stakeholders.Proven cross-functional collaboration with product, engineering, analytics, and data science teams.Self-driven and comfortable owning ambiguous problem spaces.Let op: vacaturefraudeHelaas komt vacaturefraude steeds vaker voor. We waarschuwen je voor mogelijke misleiding:* Wij zullen nooit via WhatsApp of in een videogesprek vragen om jouw persoonlijke gegevens (zoals een kopie van je ID, bankgegevens of BSN).* Twijfel je over de echtheid van een vacature of contactpersoon? Neem dan altijd rechtstreeks contact met ons op via de officiële contactgegevens op onze website.Important: job fraudUnfortunately, job fraud is becoming more common. Beware of such scams:* We will never ask for personal information (such as a copy of your ID, bank details, or social security number) via WhatsApp or during a video call. xgiwjmb * If you're unsure whether a vacancy or contact person is legitimate, please reach out to us directly using the official contact details on our website.