Analytics Engineer

About us

Traditional banking has never really given you control over your financial life. Satispay exists to change that: to empower people through finance. That means making financial services easy and accessible for over 6.5M users. We started with payments, then benefits, investing, cards... and we’re not done. Not even close. We follow the same logic every time: find a real problem, solve it properly, then look for the next one. The destination? To build the most loved financial platform in the world. If you own outcomes rather than tasks, stay close to what users need, and refuse to wait for someone else to fix what's broken — you'll find people here who work exactly in the same way. And together, you'll build something worth being proud of.

What you'll be doing

As our Analytics Engineer, you'll be the analytical backbone of this ecosystem, combining deep technical craft with strong business partnership to build core data products. Here's what that looks like in practice:

• Own critical products end-to-end - Manage the full lifecycle of warehouse data products and straightforward 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 the robust, highly auditable data models required to automate complex compliance reporting.

• Partner on platform & agentic infrastructure - Guide shared warehouse infrastructure alongside the Data Platform team, and contribute the 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.

Who we're looking for

This role needs someone with a data product owner mindset who thinks beyond the pipeline to the end user, focusing on the decisions they need to make and how the data product unlocks value.

• Technical mastery - Expert in SQL; proficient in Python for scripting, and pipeline work. You are a 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, and you treat Git and CI/CD as standard working practice.