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Staff Engineer, Data & Analytics

Staffbase•Technology
Berlin, BrandenburgVollzeitVor Ortvor 1 Monat
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📄Stellenbeschreibung

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.

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Job-Übersicht

Veröffentlicht
1. September 2026
Standort
Berlin, Brandenburg
Beschäftigungsart
Vollzeit
Arbeitsmodell
Vor Ort

Unternehmen

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Staffbase

Berlin, Brandenburg
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