Senior Product Manager – Data and Analytics

2 weken geleden


Amsterdam, Nederland TomTom Voltijd

We’re looking for a Product Manager to own the strategy, roadmap, and adoption of internal data and analytics capabilities used by product teams. You’ll work closely with engineering, data science, and business stakeholders to translate real product needs into scalable platforms and best practices.Wilt u meer weten over deze baan? Scroll naar beneden en ontdek welke vaardigheden, ervaring en opleidingseisen nodig zijn.What You'll DoOwn the vision, strategy, and roadmap for data & analytics capabilities that enable product teams to be truly data-driven and product-ledLead the end-to-end product lifecycle—from discovery and scoping through development, rollout, and continuous improvementDrive cross-team alignment and stakeholder buy-in across engineering, data science, and business teamsAdvance trusted metrics and governance shape frameworks for metric definitions, quality, monitoring, and alertingEvolve our data architecture—helping move toward data mesh-inspired models (decentralized ownership, federated governance) while balancing centralized needsContribute to key technical decisions—you’re fluent discussing data storage, APIs, event schemas, and analytics/ML needs with engineers and data scientistsChampion operational excellence—embed data quality practices, efficient pipelines, access controls, and compliance guardrails into daily workEvangelize and educate help build a data-driven culture through playbooks, enablement, and trainingWhat You'll Need8+ years in Product Management (or similar roles building data platforms/products), delivering outcomes with cross-functional teamsTechnical depth comfortable with data architectures and analytics workloads; able to discuss schemas, telemetry, storage options (warehouses/lakes), APIs, and experimentation frameworksExperience with data mesh or similar decentralized data ownership/governance models, or migrating from silos to hybrid approachesProven ability to set vision/OKRs, make clear product decisions amid ambiguity, and align multiple stakeholder groupsTrack record improving metrics quality and trustworthiness (definitions, monitoring, anomaly detection, freshness/latency) and enabling self-service analytics at scaleExposure to AI/ML enablement for product teams (agent-assisted analytics, analytics stores optimized for LLMs, vector search, etc.)Experience shaping data governance & access control across multiple systems with varying sensitivity levelsWe may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. xbpjoel Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.


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