Senior Data Platform Engineer — Diegem, Belgium
Diegem Full-time Senior Data Engineering
At a glance
Senior Data Engineering role at Ilias Solutions. Diegem · full-time.
Pay not stated Data Platform Engineer salary
RoleData Engineering
SenioritySenior
LocationDiegem
EmploymentFull-time
PostedOct 13, 2026
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Keep the live data platform and its dependent backend services stable and observable in production
- Write deployment guidance, backup steps and recovery playbooks customers can use without your help
- Add metrics, logs and health checks across Spark, PostgreSQL, MinIO and the JVM to expose failures clearly
- Build security requirements into the platform and resolve findings before releases
- Test releases across HTTP and HTTPS, with both FIPS and non-FIPS configurations, and maintain CI/CD checks
What you bring
- You can qualify for and retain the national or NATO security clearance required for this work
- You have operated Python and Spark in production, including responsibility for their runtimes
- You have used object stores such as MinIO or S3-compatible systems and lakehouse formats such as Iceberg or Hudi
- You bring practical PostgreSQL operations experience covering backup, recovery, diagnosis and schema changes
- You hold a computer science or software engineering degree, or have equivalent professional experience
Who this fits
This suits a senior engineer ready to own platform operations, security decisions and customer-facing runbooks. The role is full-time and permanent, with two on-site days in Diegem, Belgium. Clearance eligibility is required, and export-control rules may also apply.
From the employer
Hybrid (2 days on-site) · Permanent, full-timeAbout the roleWhen a warship cuts its last network link, or a forward air base goes dark, your platform still has to work. At ILIAS Solutions, you will engineer the data infrastructure, built on Python, Spark, MinIO, PostgreSQL and lakehouse table formats, that naval and air defence operators depend on in air-gapped, shipboard and disconnected environments.
What you'll do
At twelve months, FIPS and non-FIPS validation is a routine gate, not a release risk, and the runbooks you have written are the authoritative reference, not you.What you bring
- Keep the production data stack and the backend services built on top of it reliable and observable in production.
- Define and document deployment patterns, backup procedures and tested recovery runbooks that customer teams can execute independently.
- Instrument the full stack, Spark drivers and executors, PostgreSQL, MinIO and the JVM, with metrics, logs, health checks and clear failure diagnostics.
- Embed security constraints into platform design and address security findings before each release.
- Validate releases across HTTP/HTTPS and FIPS/non-FIPS environments, keeping CI/CD quality gates rigorous and release behaviour predictable.
At twelve months, FIPS and non-FIPS validation is a routine gate, not a release risk, and the runbooks you have written are the authoritative reference, not you.What you bring
- Eligibility to obtain and maintain the required national or NATO security clearance for this role (we support candidates through the clearance process).
- Production-depth Python and Spark: you own and operate runtimes, not just write jobs against them.
- Hands-on experience with object storage such as MinIO or S3-compatible stores, and lakehouse table formats such as Iceberg or Hudi.
- Operational PostgreSQL knowledge: backup, recovery, diagnosability and schema management under constraints.
- CI/CD and quality gates, rigour around releases, independent of platform; containerised development in deployment contexts.
- Degree in computer science or software engineering, or equivalent professional experience, the or-equivalent clause is genuine.
- Clear written and verbal communication with both engineers and product stakeholders; you will own design and runbook decisions and explain them.
- Air-gapped delivery experience: offline install bundles, signed packages or tooling such as Zarf; STIG-hardened hosts or FIPS-validated crypto library constraints.
- Kafka, Airflow or comparable streaming/orchestration; Scala sufficient to read Spark source and stack traces; Docker Swarm migration experience.
- Constrained-hardware deployments: single-node or few-node clusters, edge or shipboard scheduling, remote shuffle services and shuffle-heavy job tuning.