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Staffbase
Staffbase

Engineering Manager (Data & Analytics)

Job summary
Permanent contract
Berlin, Hem, Dresden
Salary: Not specified
Experience: > 5 years
Skills & expertise
Communication skills
Negotiation skills
Coaching and mentoring
Stakeholder management
Data engineering
+2

Staffbase
Staffbase

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Questions and answers about the job

The position

Job description

  • 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

Preferred experience

  • 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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