Job Description
As an Analytics Engineer, you will take ownership of the analytical transformation layer and the KPI calculation logic.
Your main responsibilities will include:
1. Structuring and modelling operational data from warehouse automation environments.
2. Translating validated KPI requirements into precise calculation rules.
3. Defining KPI granularity, filters, exclusions, time windows, data sources and interpretation limits.
4. Building and maintaining reliable transformation logic.
5. Working on database structuring and creating small Python scripts when needed.
6. Implementing data quality checks, validation rules and reconciliation logic.
7. Documenting KPI definitions, calculation assumptions and known limitations.
8. Ensuring that data models and KPI rules are version-controlled, tested and reusable.
9. Collaborating with software architects, DevOps, full-stack developers and operational stakeholders.
Qualifications
We are looking for a profile with at least 3 to 5 years of experience in one of the following areas:
10. Analytics Engineering
11. Data Engineering
12. BI Engineering with strong technical depth
13. Technical Data Analyst role with genuine data ownership
You ideally bring:
14. Strong SQL skills.
15. Good understanding of databases and data modelling.
16. Experience in defining and structuring KPIs.
17. Ability to work with operational, process-oriented or event-driven data.
18. Experience with data quality, validation rules and documentation.
19. Familiarity with Git, version control, testing or CI/CD practices.
20. Ability to create small Python scripts when needed.
21. Fluent English is required.
Experience with OLAP databases, event-driven data, IoT, warehouse automation, supply chain, logistics, MQTT or industrial data environments will be considered a strong plus.
What this role is not
This is not a purely Power BI or dashboarding role.
We are not looking for someone who only consumes data or produces visual reports.
We are looking for someone who is able to understand how data is produced, transformed, controlled and made reliable.
The right person will naturally ask the right questions:
22. Where does this data come from?
23. Can we trust this number?
24. What exactly does this KPI measure?
25. Which data should be excluded?
26. How can we prove that the calculation is correct?
27. How can we make this logic reusable and scalable?
Additional information
What do we offer you?
28. A place in an enthusiastic, young organisation with the necessary ambitions
29. The necessary freedom and opportunity to take initiative.
30. An intensive training by experienced people.
31. An attractive salary in an international environment with many benefits: Company car with fuel card/charging pass Group & health insurance Meal vouchers (8) Net allowances CAO90 Bonus Laptop iPhone + subscription 20 days of vacation plus 12 extra days for working a full year on 40h-workweek instead of 38h (32 leave days in total)
32. Satellite office in Berchem ( Antwerp )