Senior Data Engineer (Cloud Data Platform)

TALEO Consulting Group; Brussel Hoofdstad; On-site; EUR 70,000 - 110,000; Full time

Job summary

TALEO Consulting Group seeks a data engineer to join our client’s Data Platform & Engineering team. You will design and build scalable batch and streaming ELT/ETL pipelines on a modern cloud lakehouse platform, and develop data models and products across layers.

You will implement data quality checks, define SLAs, enforce GDPR controls, publish metadata to the data catalogue, and champion DataOps practices while mentoring junior engineers in a multicultural environment.

Qualifications

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

Responsibilities

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

Skills

SQL

Python

Spark/PySpark

Lakehouse platform

Databricks

Snowflake

Fabric

BigQuery

Airflow

Azure Data Factory

dbt

Kafka

GDPR awareness

English

Dutch or French

Education

Master’s or Bachelor’s degree in computer science, engineering or information systems

Tools

Airflow

Azure Data Factory

dbt

Kafka

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.

Required profile.

• 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.
• 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

We are always on the lookout for talented people to enrich our culture and growing family.