Staff Engineer, Data & Analytics
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Role details
Tech stack
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Job description
Home-Office Data Engineering Kafka MS Access Python Software as a Service (SaaS) Stakeholder Management, * 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
Requirements
- 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.
Benefits & conditions
- 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., * 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 âŹ1560
- 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 - youâll get one day off per year for supporting a social project
Job-Infos Berufsfelder Datenbankentwicklung/BI Studienfächer Informatik Informatik (Andere) Wirtschaftsinformatik Wirtschaftswissenschaften Abschluss Ausbildung Bachelor Master/Diplom IT-Gehälter Was kann ich verdienen? get in IT hat die Informationen von der Webseite des Unternehmens und ggf. sonstigen Quellen sorgfältig zusammengestellt. Diese Informationen wurden vom Unternehmen noch nicht autorisiert.Informationen fßr Unternehmen
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