Hybrid Data Platform Engineer for AI/ML Pipelines

European Tech Recruit; Brussel; Hybride; EUR 70 000 - 100 000; Plein temps

Avantages offerts par ce poste

Hybrid work

Résumé du poste

European Tech Recruit seeks a Data Platform Engineer to own the end-to-end platform powering automotive AI initiatives. You will design and operate workflows for video ingestion, metadata, GDPR compliance and dataset versioning, enabling reproducible ML experiments.

You'll build scalable pipelines, robust relational data models, APIs and dashboards that monitor data quality, usage and compliance. Collaboration with software, data science and product teams is essential to deliver secure,

Qualifications

• Strong data engineering and pipeline experience.
• Excellent relational database design skills.
• Proficient in Python for automation and APIs.

Responsabilités

• Build automated video ingestion and processing pipelines, including validation, metadata extraction and deduplication
• Design robust relational data models and metadata catalogues
• Implement GDPR and consent management, audit trails, retention and automated notifications
• Establish dataset versioning and reproducibility across ML experiments
• Build APIs and interfaces for data input, browsing and management
• Develop dashboards covering data quality, dataset usage, compliance and operational metrics
• Ensure traceability aligns with ASPICE and integrate with Codebeamer
• Deploy and operate the platform securely, including appropriate isolation of sensitive data
• Occasionally support data collection and in-car testing

Connaissances

Data engineering

Relational DB design

Python

Large media datasets

Data dashboards

GDPR handling

ML dataset lifecycles

Communication

Description du poste

European Tech Recruit seeks a Data Platform Engineer to own the end-to-end platform powering automotive AI initiatives. You will design and operate workflows for video ingestion, metadata, GDPR compliance and dataset versioning, enabling reproducible ML experiments.

You'll build scalable pipelines, robust relational data models, APIs and dashboards that monitor data quality, usage and compliance. Collaboration with software, data science and product teams is essential to deliver secure,