Senior Data Engineer (Cloud Data Platform)

Taleo Consulting
Brussel, Belgium
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Languages
Dutch, English, French
Job source

Tech stack

Artificial Intelligence Airflow Amazon Web Services Microsoft Azure BigQuery Code Review Information Systems Continuous Integration Information Engineering Data Infrastructure Extract Transform Load (ETL) Identity and Access Management
+18 more
Python (Programming Language) Meta-Data Management Standard Sql DataOps Privacy Controls Cloud Platform System Data Ingestion Azure Data Factory Snowflake Apache Spark Build Management Pyspark Information Technology Apache Kafka Data Management Software Version Control Data Pipelines Databricks

Job description

Our client’s Data Platform & Engineering team builds the data foundation for analytics and AI across four streams:

  • Data Ingestion & Integration
  • Lakehouse Modelling & Data Products
  • Data Quality & Observability
  • Security, Governance & DataOps

Your role:

  • Design and build scalable batch and streaming pipelines (ELT/ETL) on a modern cloud lakehouse platform.
  • Develop data models and data products across raw, curated and consumption layers, following domain-ownership and data mesh principles.
  • Implement automated data quality checks, testing, lineage and observability for critical pipelines.
  • Define and monitor SLAs / SLOs, manage incidents and perform root-cause analysis on data issues.
  • Apply security and privacy controls (access management, masking, encryption, retention) in line with GDPR and internal policies.
  • Publish metadata, lineage and business definitions to the data catalogue together with data stewards.
  • Champion DataOps practices (version control, code review, CI/CD, infrastructure-as-code) and mentor junior engineers.

Requirements

  • Master’s or Bachelor’s degree in computer science, engineering or information systems.
  • 5+ years in data engineering, including significant experience on Azure, AWS or GCP.
  • Strong SQL and Python; Spark / PySpark and a lakehouse platform (Databricks, Snowflake, Fabric or BigQuery).
  • Orchestration and transformation tools (Airflow, Azure Data Factory, dbt); Kafka is a plus.
  • Solid knowledge of data modelling, data quality and metadata management; GDPR awareness.
  • Fluent in English, with Dutch or French.

Soft skills:

  • Team player
  • Quick self-starter with a proactive attitude
  • Strong problem-solving and analytical skills
  • Clear communication across business and technology teams
  • Comfortable in a dynamic, multicultural environment

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