[Hiring] Senior Analytics Engineer @Finom

Role Description

As our Senior Analytics Engineer for Operations, you'll own that data end to end, the model behind it, the metrics it produces, and the trust the business places in both. This role isn't just "build the metric, ship the dashboard." We want someone who looks past the number to the process behind it, where it's manual, where it's fragile, where the right tool removes the work instead of just reporting on it. You'll have a direct line to influencing how those processes and the surrounding product actually work, not just how they're measured.

You'll sit embedded inside Operations, partnering with the TRI (Trust & Risk Intelligence) domain wherever the two overlap, while working inside the Data & Analytics team's AE guild — so you'll have the tools and the context to actually contribute, not just execute.

What You Will Be Doing

• Own the Operations data model — reconciliation, treasury, payments, lifecycle, and onboarding — turning raw operational events into documented, trustworthy data products on the DWH.
• Partner directly with Operations stakeholders on day-to-day questions, ad hoc requests, and recurring reporting, acting as their primary data point of contact — while pushing routine, repeatable questions toward self-service instead of answering the same thing by hand every time.
• Look past the metric to the process behind it — understand how everything actually works end to end, spot where manual effort or fragile handoffs are the real problem, and identify which tools (not just which query) would solve it.
• Define and maintain key metrics for reconciliation accuracy, treasury positions, payment success/failure rates, and onboarding conversion, working within the team's central metric architecture.
• Participate in data quality and governance practices for the domain.
• Bring process and product ideas to the table directly — you're close enough to the operational reality to see what should change, and this role expects you to say so and help make it happen, not just report the numbers upward.

Your First Six Months

• First month: Learn the Operations domain and how it currently works and reports, end to end. Meet your stakeholders and your teammates. Ship a first small, well-scoped fix or data product from the existing backlog to get real signal into the system quickly.
• First 3 months: Own at least one Operations sub-domain's metrics end to end. Start contributing to the shared Risk/TRI conversations, and bring your first concrete process or tooling suggestion to a stakeholder — something you noticed while getting close to the actual workflow.
• First 6 months: Operations stakeholders treat you as their data partner, not the new person. Routine checks are answered by self-service — what reaches you is what actually needs a person. You hold real, independent ownership over the data and workflows under your supervision.

Qualifications

• You've worked as an analytics engineer or senior analyst on technical projects involving data modeling on a modern data platform (Databricks, Spark, or dbt) — not just querying data others built.
• You write excellent SQL for analytical work, and you can pick up Python for anything SQL doesn't cover well.
• You're confident gathering requirements directly from operational stakeholders and turning ambiguous asks into clean, documented metrics.
• You default to precision over speed when the two are in tension — Operations data feeds regulatory and financial reporting, and being wrong quietly is worse than being slow.
• You can hold two stakeholders' definitions of "the same" metric and reconcile them, rather than picking whichever is more convenient.
• You think past the metric to the process it describes — you want to understand how the domain's tasks actually get done, spot which tool or automation would remove real work rather than just report on it, and you push for that change rather than waiting to be asked.
• You have a high level of autonomy and self-direction — you're the one who decides what needs fixing, not just how to measure it.
• AI-assisted workflows and tools are just part of how you work, not a novelty.

Nice to Have

• Background in banking, fintech, treasury, or payments operations.
• Experience working across multiple stakeholder groups with overlapping but not identical needs.
• Familiarity with regulatory or financial reporting data requirements.
• Occasional exposure to BI-layer reporting (PSM, lifecycle, or similar) when it intersects with your data products.

Benefits

• Make a genuine impact on the product.
• Join our upward trajectory, and grow with us. We provide the resources and opportunities for continuous personal and professional development, empowering you to make a genuine impact on our evolving product.
• Work in the EU. Embark on this exciting journey with us and enjoy the flexibility of traveling and working remotely or in a hybrid model across Europe.
• Become a stock options holder. Unlock your inner entrepreneur and align your aspirations with ours through our Stock Options Program. This exciting opportunity is available to every team member, from junior team members to our founders.
• Receive unwavering support and care. Finom stands by you at every step, embodying our commitment to your well-being and success reflected in our modern, friendly, and eco-conscious corporate culture. We offer constant support and care to ensure your Finom experience is successful and fulfilling.
• Work & Swim program. Immerse yourself in our exclusive Work & Swim Program. Spend one month in a comfortable corporate apartment in enchanting Cyprus. It's the ideal opportunity to strike the perfect work-life balance while enjoying breathtaking Mediterranean views.

Equal Opportunity Statement

At Finom, we're an equal opportunity employer and value diversity at our company. We embrace diversity and invite applications from all walks of life. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, disability status, or other applicable legally protected characteristics.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.