Senior Analytics Engineer - Data Governance

Our mission and customers: We are creating the freedom for SMEs to succeed by delivering Europe's leading finance workspace with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 55,000+ reviews. Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75 (more about our culture here).

Our journey: Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000+ customers across 8 European countries. We have been profitable since 2023, and we are just getting started.

Our beliefs: We hire for skills and potential. With 80+ nationalities, 45% women, of which 56% of women in our leadership team, diversity isn't a program; It's who we are. We've built a discrimination-free hiring process because the best teams are built on merit.

AI at Qonto: AI is deeply embedded in how we work (here) - Every Qontoer gets unlimited access to the best AI tools. We want people who experiment without waiting for permission, push AI beyond the obvious, know when to trust it, and when to question it.

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️ Mission: Join us as Analytics Engineer- Data Governance and become the architect of Qonto's data trust layer as we make our transition to a fully licensed bank.

You will own end-to-end the Data Governance framework - defining rules, implementing controls, monitoring quality, and driving remediation across the company - so that every compliance report is reliable and every business decision is grounded in trusted data.

You will work closely with Alice Fresko, our Head of Analytics Engineer, and with Paul, our Staff Analytics Engineer, and sit at the intersection of Data, Product, Engineering, and Compliance. This is a first-of-its-kind role at Qonto: you won't inherit a mature process, you'll build it.

️ As an Analytics Engineer at Qonto, you will:

• Build and operate the Data Governance framework - establish data quality rules, standards, and controls across the company's critical datasets, with a clear focus on banking compliance requirements (audits, regulatory reporting)
• 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 reporting for data owners and stewards, run cadenced follow-up rituals with stakeholders, and ensure action plans are executed - without being annoying about it
• Drive adoption of Data Governance tooling - own Data governance 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; this role is highly automatable and we expect you to leverage that

️ What you can expect:

• You're building from scratch - the framework is in its early stages. You won't be inheriting a playbook; you'll be writing it. That means high autonomy, high ownership, and a real "first-of-its-kind" trajectory
• Compliance is the bar- The outputs of your work will ensure Qonto is ready to transition from Payment institution to Credit Institution. The outputs of your work feed into regulatory reporting and audit reviews. Precision, rigor, and traceability aren't optional
• Broad stakeholder exposure - you'll work daily with senior PMs, Backend, domain data owners at senior leadership level and Risk & Compliance teams.. Strong influence and communication skills matter as much as your technical chops
• AI is the multiplier - we use AI daily at Qonto (read our vision). We expect you to use it too - not just as a coding assistant, but to automate the repeatable parts of data governance: monitoring, alerts, follow-up chasing, test generation
• Growth potential - depending on company scale and automation maturity, this role can evolve to Staff-level scope and potentially lead a small team (+1 junior in ~2-3 years)

️ About your future manager: Your manager will be Alice Fresko, our Head of Analytics Engineer.

Alice joined Qonto in 2021 and has grown from Data Analyst to Lead Analytics Engineer, playing a key role in shaping our data modeling practices and analytics engineering culture. She brings both technical depth and a strong vision for data foundations, and promotes a culture of knowledge sharing and high standards for data quality. Her leadership style is collaborative and direct.

You can hear her talk about Analytics Engineering (in French) in this podcast.

️ About You

• Analytics Engineering expertise - you are strong in dbt and SQL (our core stack). You've shipped production-grade data models and tests, and you're comfortable owning pipelines end-to-end. Python for automation is a plus, not a requirement
• Stakeholder management - you know how to run rituals, follow up persistently without burning bridges, communicate across technical and non-technical audiences, and drive cross-functional programs with no direct authority
• Process and compliance mindset - you care about precision, documentation, and "what can go wrong" thinking. You're comfortable in environments where the output has regulatory consequences
• AI-native work style - you use AI tools in your daily work beyond just chatting: code generation, automation, agents. Ideally, you've built or configured a workflow or agent in the past few months
• Appetite for building - you're excited by ambiguity and blank pages. You want to be the person who shapes the answer, not the one who inherits it
• French speaker is a key requirement for this job

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.

By applying, you agree that Qonto processes your personal data to assess your application. Your data is kept for up to 2 years in our candidate pool. Read our Privacy Notice for full details.

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On average, our hiring process lasts 20 working days. More information on our candidate journey here

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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.