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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