Data Engineer (Data Engineering Platform) - Maastrich...

Duties & Role:

· 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

Skill, Knowledge & Experience:

• 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

• Excellent English (min. C1 level)

• Bachelor’s degree in:

• Computer Science / IT / Software Engineering (or equivalent)

• Strong experience delivering data pipelines in production environment

Desirable 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)

Location: Maastrich (Near Site)