Staff Engineer, Data & Analytics

staffbase· Data Engineering
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📍 Chemnitz, Sachsen, Germany

About this role

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.

As a Staff Engineer in our Data & Analytics team, you will drive the technical direction of our data platform and analytics capabilities. This is a hybrid role combining hands-on technical leadership with people leadership.  You will work closely with the Director of Engineering and cross-functional stakeholders to advance our data infrastructure and lay the foundations for AI-powered product features.

Our environment

  • Work alongside skilled, data-passionate engineers in a team that values collaboration
  • A flexible, agile environment with a strong focus on work-life balance
  • You will have real ownership and influence over data architecture 
  • We are building toward a distributed, self-service data platform model – you will help shape how that evolves.
  • Data is a strategic asset at Staffbase: valued, actively growing, and directly enabling our AI product roadmap.

What you'll be doing

  • Drive the technical direction of our data platform – leading architecture decisions, sequencing, and delivery in collaboration with Engineering, Product, and Design stakeholders
  • Support and develop a team of 4–5 engineers: providing technical mentorship, unblocking delivery, and helping build a product-minded engineering culture.
  • Own and evolve the data infrastructure: data lake, data foundations, semantic layer, and data governance – building a solid base for AI and analytics features
  • Lead streaming adoption across the team, bringing hands-on expertise to an area the team is actively developing
  • Apply and advance strong data modeling practices across the platform.
  • Prioritize and mediate effectively with product stakeholders – advocating for the right technical decisions and sequencing of work
  • Contribute to the evolution of our self-service data platform approach, driving the cultural and technical shift toward distributed data ownership
  • Collaborate across the broader staff engineering community on cross-cutting architectural decisions

What you need to be successful

  • 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.
  • Experience with streaming technologies (e.g. Kafka) – hands-on exposure is a strong plus
  • 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 – you are comfortable pushing back, negotiating roadmaps, and finding constructive compromises with product teams
  • A product-minded engineering mindset: able to balance technical rigour with pragmatic prioritization.
  • Leadership experience or ambition: you are comfortable guiding engineers and driving delivery

Nice to have

  • 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.

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

Frequently Asked Questions

Is the salary disclosed for the Staff Engineer, Data & Analytics position at staffbase?
The salary for this Staff Engineer, Data & Analytics role at staffbase is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Staff Engineer, Data & Analytics position at staffbase located?
This Staff Engineer, Data & Analytics role at staffbase is based in Chemnitz, Sachsen, Germany. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Which team or department does the Staff Engineer, Data & Analytics at staffbase belong to?
This Staff Engineer, Data & Analytics position is part of the Data Engineering department at staffbase. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Staff Engineer, Data & Analytics position at staffbase?
Click the "Apply Now" button on this page. You will be redirected to staffbase's official application portal hosted on greenhouse where you can submit your application directly.
When was the Staff Engineer, Data & Analytics job at staffbase posted?
This Staff Engineer, Data & Analytics position at staffbase was posted on Jun 30, 2026. Apply as soon as possible — early applications are often reviewed first.
Staff Engineer, Data & Analytics
staffbase
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