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Tech Stack
Tools & technologiesAirflowAWSAzureCloudGoogle Cloud PlatformPythonSQLTerraform
About the role
Key responsibilities & impact- Own the architecture of data and AI platforms for our clients: ingestion, storage, transformation, orchestration, serving, observability, and security.
- Set up and harden production environments on modern cloud stacks (AWS, Azure, GCP) with tools like Databricks, Snowflake, Microsoft Fabric, dbt, Airflow, and the surrounding ecosystem.
- Design and implement the AI Platform layer: model serving, feature stores, RAG pipelines, vector stores, evaluation and monitoring, cost and latency controls, and the guardrails around LLM-based applications.
- Act as senior technical support across active engagements: code reviews, troubleshooting on hard problems, performance tuning, and unblocking junior and mid-level engineers.
- Coach the team. Raise the engineering bar through pairing, technical write-ups, internal sessions, and clear standards.
- Engage directly with client tech leads, architects, and CTOs. Translate business intent into a defensible technical design.
- Contribute to proposals and scoping discussions when senior technical credibility is needed.
- Help shape our point of view on data and AI platforms, and feed it back into our offerings.
Requirements
What you’ll need- a master's degree in engineering, computer science, mathematics, statistics, or a related quantitative discipline
- at least 5 years of professional experience in data engineering or platform engineering
- Designing and operating production data platforms on at least one major cloud (AWS, Azure, or GCP).
- Hands-on work with a modern data stack: Databricks, Snowflake, Microsoft Fabric, dbt, Airflow or equivalent, plus solid SQL and Python.
- Building or operating components of an AI / ML platform: model deployment, inference infrastructure, RAG pipelines, vector databases, evaluation and observability of LLM applications.
- CI/CD, infrastructure as code (Terraform or equivalent), and DevOps practices applied to data.
- Data modeling and analytics engineering patterns (medallion, dimensional, contract-driven pipelines).
- Security and governance basics: IAM, secrets management, lineage, data quality, GDPR-aware design.
- Working directly with client stakeholders in a consulting or in-house lead role.
- Fluency in English (our internal working language) is required, plus fluency in French or Dutch. Strong proficiency in Dutch is particularly valued.
- Valid type B driving license (Belgian car license) or equivalent.
- Eligibility to work in Belgium and the European Union (please be aware that we cannot provide relocation support).
Benefits
Comp & perks- Competitive package: variable incentives, mobility budget, phone subscription, laptop, and meal vouchers
- Flexibility on remote working options, as long as it fits with our clients' best interests and team coaching needs
- Training and development: a roadmap co-designed with you, balancing your personal interests with the skills required by the role
- Supportive structure and transparency: we practice radical candor. We care personally about everyone, and we challenge each other constructively and directly.
- Modern tools: up-to-date hardware and software so technology is never the bottleneck.
- Oh, and a little bit of fun too: we take our work very seriously, but we're not afraid to laugh at ourselves. Life is too short.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringplatform engineeringSQLPythonCI/CDinfrastructure as codedata modelinganalytics engineeringAI platform componentsobservability
Soft Skills
coachingtechnical supportcommunicationproblem-solvingcollaborationclient engagementtechnical credibilitydesign translationstandards enforcementteam leadership
Certifications
master's degreetype B driving license