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# Data Engineer - Portfolio Integration and Decision Support for NATO

- **Company:** Wlg Group Bekijk Alle Vacatures
- **Location:** Brunssum, Netherlands
- **Contract:** Permanent contract
- **Skills:** Spreadsheets, Information Systems, Information Engineering, Data Integration, Data Visualization, Decision Support Systems, Digital Data, SQL Databases, Systems Integration, Information Technology
- **Published:** September 19, 2026
- **Apply:** https://www.careerjet.nl/job/nl10f3ff0a0e4e6fd4f6b03c52bc7804e7/eaa

## About the Role

* A university degree in data science, computer science, information systems, engineering, operations research, statistics or a closely related field, or equivalent experience.
 * Recent end-to-end delivery you did personally, from identifying the need to an operational solution.
 * At least three of the last five years in data integration and engineering, with hands-on work inside the last two.
 * At least two of the last five years using SQL and an analytical language, hands-on inside the last two.
 * Experience designing or building digital data-collection and workflow solutions.
 * At least three of the last five years personally building business intelligence products.
 * Hands-on data modelling, data quality and governance work.
 * Experience documenting and handing over a solution so it survives without you.
 * At least two of the last five years working directly with operational users and programme staff.
 * Fluent professional English.

## Description

A multinational defence organisation runs a large infrastructure and capability portfolio, and the information behind it lives in too many places. This is a hands-on data engineering seat: build the integration, model the data, and turn it into decision support that holds up.
What you would be doing

 * Hands-on data integration, engineering and analysis across the portfolio, starting with the infrastructure programmes.
 * Working directly with programme managers, analysts and data owners to understand which decisions need which information.
 * Designing, building, testing and maintaining repeatable pipelines that ingest, transform and reconcile data from several sources.
 * Building the data models, common definitions, business rules and quality controls that make the output trustworthy.
 * Prototyping digital data-collection applications that replace spreadsheet-heavy manual reporting.
 * Building dashboards, metrics and visualisations that show programme status and dependencies.
 * Applying descriptive and diagnostic analysis, and predictive techniques where the decision genuinely needs them.
 * Integrating portfolio information with authoritative enterprise sources through approved mechanisms.
 * Finding and fixing data quality, ownership, lineage and governance problems.
 * Documenting sources, models, transformations and operating procedures so somebody else can run it.


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