Data Platform Engineer

Qonto; Paris; Sur place; EUR 65 000 - 100 000; Plein temps

Résumé du poste

Qonto is building a centralized data platform to serve thousands of users across Europe. As a Data Solution Engineer, you will own data pipelines end-to-end—from ingestion into Snowflake to exposure via Trino and Metabase—while automating and stabilizing the stack.

You will enable self-service for teams by creating reusable building blocks, setting data quality contracts, and running duty hours to ensure reliable data for business decisions.

Qualifications

• 3+ years of experience in Data or Software Engineering shipping data pipelines and services in production.
• Strong in Python and understanding of data infrastructure including warehouses, query engines, and orchestrators.
• Experience running open-source data tools (orchestration, query engines, BI) and comfort debugging infrastructure.
• Ability to take ownership from rough need to shipped solution and manage stakeholders.

Responsabilités

• Deliver end-to-end data solutions from ingest to production, exposing data through Trino and Metabase and automating workflows.
• Make self-service real by creating reusable, well-documented building blocks for teams.
• Act as the trusted interface for data consumers through duty and Office Hours and triage requests.
• Own data quality, contracts, tests, and SLAs; investigate incidents to root cause.

Connaissances

Python

SQL

Airflow

Snowflake

Kubernetes

OpenMetadata

Outils

Airflow

Snowflake

Trino

Metabase

Kubernetes

OpenMetadata

AWS

Description du poste

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.

Mission: Join us to build the data solutions that serve more than 600,000 customers.

As a Data Engineer, you make data safe, fresh, and self-service for the almost 2,000 Qontoers who rely on it every day.

The team: You will join the Data Platform team: Data Platform Engineers , Data Engineers and Data SREs . We own our stack end to end - Trino, Metabase, Airflow, OpenMetadata and more are deployed, run and maintained in-house by the team.

As a Data Solution Engineer at Qonto, you will:

• Deliver end-to-end data solutions: You will own data solutions from the need to production - ingestion into Snowflake, exposure through Trino and Metabase, and the automation around them - for business-critical use cases.
• Make self-service real: You will turn recurring manual requests into reusable, documented, low-maintenance building blocks, so teams stop asking and start serving themselves.
• Be the trusted interface for data consumers: You will run our duty and Office Hours, qualify incoming requests, and decide what deserves a quick fix, a proper solution, or a platform change.
• Own data quality and freshness: You will define contracts, tests and SLAs on the data you ship, and investigate pipeline incidents through to root cause rather than symptom.
• Run our open-source stack: You will manage the open-source tools the Data Platform team owns, deploys and maintains - Trino, Metabase, Airflow, OpenMetadata and more - and keep them stable for production use cases.

What you can expect:

• A central role: You will sit at the intersection of the platform and the whole company, in a mature environment where your work directly changes how Qonto decides and operates.
• Modern tech stack: A state-of-the-art cloud-native stack - Python, SQL, Snowflake, Airflow, Trino, Metabase, OpenMetadata, Kubernetes, AWS.
• High autonomy: You will join a team of senior engineers where ownership is key; you will be trusted with important topics from day one.
• Hyper-growth context: You will work on the challenges of scaling data for a leading European fintech, on a platform serving thousands of users daily.

About your future manager:

You will report to Charles , who leads the Data Platform team. He has been building Qonto's data stack for years and knows it end-to-end, so the technical guidance you get is first-hand. As a manager, he values autonomy and acts as a facilitator: he gives the team the space to own its topics and step up, and he is there when a decision needs a second pair of eyes.

About You:

• Experience: You have 3+ years of experience in Data or Software Engineering, having shipped and operated data pipelines and data services in production.
• Technical mastery: You are strong in Python , and you understand data-specific infrastructure and solutions - how a warehouse, a query engine and an orchestrator actually behave, and which one is the right answer to a given need.
• Tooling expertise: You have run open-source data tools yourself - orchestration, query engines, BI - with Airflow and Snowflake preferred, and you are not afraid to debug the infrastructure under them, where experience with Kubernetes and AWS makes the difference. You are comfortable with Git-based workflows and CI/CD.
• End-to-end ownership: You take a project from a rough need to a shipped solution: you do the product management yourself - challenge the request, scope it with the stakeholder, define what gets built - and then you build it yourself.
• AI fluency: You use AI tools daily in your engineering work (c