Analytics Engineer

Editx; Diegem; Hybrid; EUR 63,000 - 95,000; Full time

Job summary

Editx in Belgium is seeking an Analytics Engineer to split time between embedding with a defence client and contributing to the Product Engineering Team. You will turn raw operational data into dashboards and insights that operational teams rely on, owning the SQL layer end-to-end and applying Python for data transformation.

The rotation structure provides on-site ownership with team backup, in a hybrid setup (2 days on-site, 3 days from home), for a permanent full-time role.

Qualifications

• Proven ability to design and implement analytical data models.

Responsibilities

• Own the SQL layer end-to-end from raw data to production-ready models.
• Build analytical and dimensional models for asset tracking, maintenance workflows, readiness reporting, and mission planning.
• Author and publish dashboards in cooperation with client stakeholders for a defence environment.
• Apply Python for data transformation and integration glue work.
• Translate requirements from French- and Dutch-speaking client teams into analytical outputs.
• Maintain testing and technical documentation during on-site rotations.

Skills

SQL

Python

Dashboards

Data modeling

Tools

SQL

Python

Job description

Opportunity

€63,000-€95,000 gross/year · Hybrid (2 days on-site per week, at client premises or company office; 3 days from home) · Permanent, full-time

The systems that track assets, flag maintenance needs and inform mission readiness do not run on gut feeling, they run on clean data and sharp analysis. As Analytics Engineer you will split your time between being embedded at a defence customer site as part of a structured Forward Deployed Engineer team and contributing to the Product Engineering Team, turning raw operational data into the dashboards and insights that operational teams actually rely on. The rotation structure means you carry real on-site ownership while a full team provides backup and coverage; you are not alone.

Your Mission

• Own the SQL layer end-to-end, from raw source data through to production-ready models, with performance and maintainability as the standard.
• Build and maintain analytical and dimensional models that underpin asset tracking, maintenance workflows, readiness reporting and mission planning, datasets that operational teams act on, not prototypes.
• Author and publish dashboards and views in close cooperation with client stakeholders, translating operational requirements into analytical deliverables that are clear, accurate and fit for a defence environment.
• Apply Python for data transformation, lightweight analysis and integration glue work, keeping pipelines reliable and documented.
• Elicit and interpret requirements directly from French- and Dutch-speaking client teams when forward deployed, then translate those needs into concrete analytical outputs.
• Own testing and technical documentation during on-site rotations, with clean handover to the wider engineering, testing and documentation teams between deployments.

What success looks like

Over time, the client teams you support will reach for your dashboards first because the data behind them is trustworthy and the models are built to last. Requirements you gather on-site translate cleanly into working deliverables. Domain experts recognise that you understood what they needed - not just what they said. The components you build are documented well enough that the wider team can maintain, extend and take them into operational use without relying on your recall.