Senior Data Engineer – Maastricht, NL

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

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