Staff Engineer, Data & Analytics
HybridBerlin, State of Berlin, Germany
Job Summary
Drive the technical direction of the data platform by leading architecture decisions, sequencing, and delivery in collaboration with Engineering, Product, and Design stakeholders. Own and evolve the data infrastructure, including the data lake, foundations, semantic layer, and governance, while advancing streaming adoption and applying strong data modeling practices across the platform. Support a team of 4–5 engineers through technical mentorship, unblocking delivery, and fostering a product-minded engineering culture. Prioritize work with product stakeholders to advocate for the right technical decisions and sequencing. This hybrid role combines hands-on technical leadership with people leadership within a distributed, self-service data platform model. You will help shape the evolution of this approach and collaborate on cross-cutting architectural decisions.
Required Qualifications
- Proven experience at Staff Engineer level or equivalent in a data engineering context
- Strong architectural understanding of data platforms: data lakes, data foundations, data governance, and orchestration
- Solid data modeling skills and the ability to raise this as a team-wide standard
- Experience working with large-scale datasets commensurate with a sizeable B2B SaaS customer base
- Python proficiency and comfortable working across a modern data stack
- Strong stakeholder management and communication skills
- A product-minded engineering mindset
- Leadership experience or ambition
Desired Qualifications
- Experience with streaming technologies (e.g. Kafka) – hands-on exposure is a strong plus
- Experience with data governance for AI agents – understanding guardrails, access control, and safety considerations for agentic analytics
- Prior exposure to self-service data platform models and distributed data ownership strategies
- Experience in a product-led SaaS environment
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