CDI - Analytics Engineer - H/F/X

We are looking for an Analytics Engineer (m/f/d) to join our team as soon as possible.

About the Role :

We're looking for a Data Analyst (1–5 years) to join our Data team and turn raw operational data into actionable insights that drive product and business decisions.

In practice, the role involves a high volume of SQL queries and analytical requests from Product, Operations, and Support — translating business questions into data, fast. The role involves little modelling today, but sits at the intersection of analysis and engineering: we're actively building more robust, reproducible, and version-controlled pipelines, and you'll be part of shaping that.

We also have an AI-first culture: we actively push our teams to experiment with and build custom AI-powered solutions. If you identify as a Data Scientist or Analytics Engineer who enjoys the analytical grind but wants to work in an environment that's evolving fast, you'll find real room to grow here.

You'll be expected to combine technical rigour with business curiosity, and to ship things that actually get used.

Your Team :

You'll join a data team of 4 data scientists, embedded in a broader tech organisation of ~30 people. We work closely with Product, Operations, and Support to answer the questions that matter. We value:

• Ownership of the full data chain, not just one step in it

• Clear, honest communication of uncertainty and tradeoffs

• Practical solutions over theoretically perfect ones

• Continuous improvement in tooling, craft, and engineering practices

What You'll Do :

• Query, explore, and transform data in Databricks (SQL + Python) to produce reliable datasets and analytical outputs

• Handle a high volume of data requests from Product, Ops, and Support — with speed and rigour

• Build and maintain data pipelines and transformation logic, with attention to quality and reproducibility

• Work with Metabase to design and maintain dashboards for business stakeholders

• Translate analytical findings into clear, actionable recommendations for non-technical audiences

• Contribute to data quality practices: testing, documentation, anomaly detection

• Participate in our AI-first culture — experiment with and help build custom AI-powered solutions to automate and augment our workflows

• Leverage AI-assisted coding tools (Cursor, GitHub Copilot, Claude Code or equivalent) to move faster while maintaining quality