Staff Engineer, Data & Analytics (f/m/d)

## 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