Senior Analytics Engineer – Data Governance

About the Role

Analytics Engineer – Data Governance. In this role you will be the architect of Qonto’s data trust layer as the company transitions to a fully licensed bank.

Responsibilities

• Build and operate the Data Governance framework – define data quality rules, standards, and controls across critical datasets, focusing on banking compliance requirements.
• Implement and maintain data quality checks – design and ship dbt tests and source‑level controls (e.g., postcode validity, age ranges, referential integrity) that catch issues before they reach compliance reports.
• Own the monitoring & remediation loop – produce regular data quality reports for data owners and stewards, run cadence follow‑up rituals with stakeholders, and ensure action plans are executed.
• Drive adoption of Data Governance tooling – own the tools as the source of truth for the data catalogue and quality controls; clarify ownership, build the operating model, and keep it alive.
• Scale the program through AI and automation – actively reduce manual work by building/configuring automated checks, monitoring pipelines, follow‑up workflows, and reporting logic.

What you can expect

• High autonomy and ownership – you will build the framework from scratch and write its playbook.
• Compliance focus – your work ensures Qonto meets regulatory reporting and audit requirements for the transition from Payment institution to Credit Institution.
• Broad stakeholder exposure – daily interaction with senior product managers, engineers, domain data owners, and Risk & Compliance teams.
• AI as a multiplier – you will use AI tools beyond coding assistants to automate repeatable parts of data governance.
• Growth potential – depending on company scale and automation maturity, the role can evolve to Staff‑level scope and potentially lead a small team (+1 junior in 2–3 years).

About You

• Analytics Engineering expertise – strong in dbt and SQL; have shipped production‑grade data models and tests; comfortable owning end‑to‑end pipelines; Python for automation is a plus.
• Stakeholder management – able to run rituals, follow up persistently without burning bridges, communicate across technical and non‑technical audiences, and drive cross‑functional programs without direct authority.
• Process and compliance mindset – care about precision, documentation, and “what can go wrong” thinking; comfortable where output has regulatory consequences.
• AI‑native work style – routinely use AI tools in daily work for code generation, automation, and agents; ideally built or configured a workflow or agent recently.
• Appetite for building – excited by ambiguity and blank pages; want to shape the answer, not inherit it.

EEO Statement

At Qonto, we understand that true diversity isn’t just about ticking boxes on a hiring checklist. Apply regardless of the boxes you tick – who knows? You may have the missing piece of the puzzle we’ve been searching for all along.

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