Engineering Manager, Data & Analytics

Job description

### **About Staffbase** We inspire people to achieve great things together. Our mission is to help organizations unlock the power of inspirational communication with the first **AI-native Employee Experience Platform**. Our **industry-leading and award-winning agentic AI communications channels** - intranet, employee app and email solutions - create engaging experiences that connect and empower employees. Headquartered in Chemnitz, Germany and New York City, with offices in Berlin, London, Sydney, Tokyo, Prague, and Minneapolis–St. Paul, our diverse team of 550+ employees supports 1,500+ customers—reaching over 14 million employees—in transforming their employee experience. We are proud to be a **Unicorn** company—privately valued at over $1 billion—demonstrating strong growth, innovation, and lasting impact in our industry. Together, we’re shaping the future of workplace communication. **Engineering Manager – Data & Analytics** 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. **Our environment** - 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 **What you'll be doing** - 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 **What you need to be successful** - 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 - A genuine player-coach mindset - Strong stakeholder management skills. You thrive in negotiation, can push back confidently, and know how to reach workable compromises with product teams - Solid data modeling skills and the credibility to make it a team-wide standard - Experience managing or developing engineers. Coaching technical fundamentals and growing product thinking - Strong communication skills and the ability to drive a cultural shift toward distributed, self-service data ownership - Comfort operating across both platform and product delivery contexts **Nice to have** - 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) **What you'll get** - *Competitive Compensation* - we offer attractive salary packages including LTIP (unit-based Long Term Incentive Plan) - *Flexibility* - we offer flexible working time models and the option of hybrid work, and support this with a yearly flex work allowance of €1560 - *Recharge* - with 31 vacation days annually (incl. one floating holiday), plus pro rata fully paid Fridays off during August - *Support*-we offer offering a company pension scheme - *Volunteers Day*- you’ll get one day off per year for supporting a social project ###