SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: EUR 48,000 - 54,000 / annual
Satispay is a fintech platform serving 6.5M+ users, offering payments, benefits, investing, and cards. The company is building the most loved financial platform in the world by solving real problems for users and refusing to accept broken systems.
As Analytics Engineer, you will be the analytical backbone of the organization, combining technical expertise with strong business partnership to build core data products. Your responsibilities include:
- Own critical data products end-to-end: manage the full lifecycle of warehouse data products and ingestions, ensuring lineage, PII handling, and auditability are foundational
- Enable the Data Mesh: maintain shared dimensional models and central semantic metrics so definitions are registered once and consumed seamlessly across domains
- Automate regulatory reporting: build and maintain robust, highly auditable data models required to automate complex compliance reporting
- Partner on platform and agentic infrastructure: guide shared warehouse infrastructure alongside the Data Platform team, and contribute vital context that internal warehouse maintenance agents depend on
- Refuse to be a bottleneck: intervene proactively when you are the sole holder of knowledge, sharing it through rigorous documentation and code review
You will work in a fast-moving environment where evolution never stops. The role is hybrid (two days per week in-office on Tuesday and Thursday, with flexibility to request additional remote time).
REQUIREMENTS:
- Expert in SQL; proficient in Python for scripting and pipeline work
- Strong data modeler with experience designing scalable, future-proof models that serve multiple stakeholders and use cases
- Deep experience with dbt or other semantic modeling tools
- Familiarity with workflow orchestration
- Treat Git and CI/CD as standard working practice
- Exceptional communicator: comfortable presenting methodology and findings to both technical and non-technical partners, including executive leadership
- Proven ability to drive cross-functional alignment
- Self-starter who takes ownership and drives projects forward with minimal oversight
- Working fluency with AI-assisted development (Claude, Cursor) and grounded view of where it adds durable value
NICE-TO-HAVES:
- Prior experience as a Data Engineer
- Time spent in FinTech or highly regulated data environments
- Exposure to LLM tooling built on a data warehouse
- Experience with dashboard tools like Looker, Hex, or Tableau
