Senior Data Engineer – Maastricht, NL
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Summary
Consulting role for a Senior Data Engineer who designs, builds, and operates batch and streaming data pipelines and lakehouse/warehouse solutions on Databricks, dbt, PySpark, Python, and SQL in a safety-critical client environment in Maastricht, with focus on data quality, orchestration, and production deployment.
Project Overview
The consultant will support the development and operation of a Data Engineering Platform in a safety‑critical and business‑critical environment.
The role focuses on building, maintaining, and optimizing scalable data pipelines, ensuring data quality, and enabling efficient data processing for analytical use cases.
Key Responsibilities
- Design, build, and maintain data pipelines (batch and streaming)
- Develop and manage data transformation and modeling workflows
- Deploy and maintain production-grade data solutions
- Work with distributed data processing platforms (e.g., Databricks)
- Ensure data quality, reliability, and performance optimization
- Collaborate with stakeholders to translate business needs into technical solutions
- Support data platform architecture evolution (lakehouse / warehouse)
- Monitor pipelines and troubleshoot bottlenecks or failures
- Ensure compliance with data governance, security, and confidentiality policies
- Document solutions and communicate clearly with technical and non‑technical stakeholders
Requirements
Mandatory
- Minimum 5 years of experience in data engineering
- Strong experience in:
- Python
- SQL
- PySpark
- Minimum 3 years of experience with dbt (data build tool) including:
- Data transformation
- Data modeling
- Testing
- Deployment in production
- Minimum 3 years of experience with Databricks or similar distributed processing platforms
- Computer Science / IT / Software Engineering (or equivalent)
- Strong experience delivering data pipelines in production environments
Optional / Advantageous Skills
- Experience with Oracle databases and dbt adapters (e.g., dbt-oracle)
- Experience designing data warehouses / lakehouses (Snowflake, BigQuery, Delta Lake)
- Experience with Kafka / Kafka Connect (streaming pipelines, real‑time ingestion)
- Experience with orchestration tools:
- Apache Airflow
- Databricks Workflows
- Experience with Infrastructure as Code (Terraform, Pulumi)
- Experience with cloud platforms:
- Azure
- AWS
- GCP
- Knowledge of data governance and metadata tools (e.g., Collibra)
- Ability to translate complex data concepts into business-friendly language
- Strong problem-solving and analytical thinking
- Proactive and self-driven approach to resolving issues
- Ability to work in changing priorities and complex environments
- Strong team collaboration skills
- High attention to data protection and confidentiality