S
Staffbase
Engineering Manager (Data & Analytics)
Skills
Data EngineeringKafkaData AnalysisAI
16 hours ago
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Important information
Contract type:
Permanent
Location:
Berlin, Germany
Work mode:
Onsite
Published on:
22 October 2026
What they need
- As Engineering Manager for our Data & Analytics team, you will lead a team of 4-5 engineers while staying meaningfully hands-on as a technical player-coach
- This is not a traditional management role. You are someone with a strong and senior data engineering background who genuinely wants to step into management
- You will own the team’s delivery, drive stakeholder alignment, and bring the technical depth needed to develop your team and keep us on the right track
- You will work closely with the Director of Engineering and product stakeholders, on sequencing, prioritization, and roadmap negotiation — with enough technical grounding to make sound decisions and mentor engineers day to day
- Data operates on two fronts: maintaining and evolving a self-service data platform, and delivering as a product team
- While the overall architecture direction is established for the near term, you’ll shape the details and influence the technical direction as the roadmap extends into 2027 and beyond
- You are the voice on data. Driving delivery and managing the interfaces with the broader staff engineering community available to support on high-level architectural input
- Data governance for AI agents is an emerging and fast-growing priority — a technically exciting area we’re starting to build into
- Lead and develop a team of 4-5 engineers: coaching, unblocking delivery, and building a product-minded data engineering culture
- Own the team’s roadmap sequencing. Negotiating priorities with product stakeholders, pushing back where needed, and finding constructive compromises
- Mediate between platform and product demands: the team operates across data platform and product delivery simultaneously, and you will balance both
- Bring hands-on experience in Data streaming to guide the team through an active transition
- Raise the bar on data modeling across the team
- Drive the cultural and technical shift toward distributed data ownership, helping product teams progressively own their own data
- With your extensive Data Engineering experience you will collaborate with the broader staff engineering community on cross-cutting architectural decisions where needed
- Build the foundations for AI data governance — as agentic analytics becomes customer-facing, you will need to think through guardrails, access control, and safety for AI agents interacting with data- Solid data modeling skills and the credibility to make it a team-wide standard
- Proven experience at Staff Engineer level (or equivalent) in a data engineering context. You have been deep in the technical work and now want to lead people
- Strong stakeholder management skills. You thrive in negotiation, can push back confidently, and know how to reach workable compromises with product teams
- A genuine player-coach mindset
- Comfort operating across both platform and product delivery contexts
- Strong communication skills and the ability to drive a cultural shift toward distributed, self-service data ownership
- Experience managing or developing engineers. Coaching technical fundamentals and growing product thinking
- Experience with data governance for AI agents — guardrails, access control, and safety considerations for agentic analytics
- Familiarity with data lakes, semantic layers, and orchestration tooling at scale
- Experience in a product-led B2B SaaS environment
- Hands-on streaming experience (e.g. Kafka or Flink)
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