Senior Data Engineer – Maastricht, NL

RMM Consulting Group; Maastricht; Hybrid; EUR 70,000 - 100,000; Full time

Job summary

RMM Consulting Group seeks an experienced Data Engineer to design, build and operate scalable data pipelines in a safety-critical environment. You will own data transformation workflows, enable efficient analytics, and drive production-grade data solutions using Databricks and dbt.

The role requires strong Python/SQL/PySpark skills, 5+ years in data engineering, and a track record of delivering reliable data platforms in complex settings.

Qualifications

• 5+ years of experience in data engineering.
• Strong experience in Python, SQL and PySpark.
• Minimum 3 years of experience with dbt (data build tool) including transformation, modeling and production deployment.
• Minimum 3 years of experience with Databricks or similar distributed processing platforms.
• Computer Science / IT / Software Engineering (or equivalent).
• Experience delivering data pipelines in production environments.

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.

Skills

Python

SQL

PySpark

Data pipelines

Data modeling

Education

Bachelor's degree in CS/IT/Software Engineering

Tools

Databricks

dbt

Job description

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