Data Engineer — Lakehouse & Analytics Platform Builder

Harnham; Eindhoven; Hybrid; EUR 59,000 - 72,000; Full time

Benefits offered by this job

Competitive salary

Impact at scale

Collaborative data team

Growth opportunities

Job summary

Harnham Eindhoven is seeking a Data Engineer to build analytics-ready datasets and semantic models, enabling scalable analytics across a large customer base. You will develop ETL pipelines using SQL and Python (or PySpark), implement lakehouse architectures, and ensure data security with multi-tenant and row-level controls.

Collaborate with analysts and stakeholders to translate requirements and drive data governance and quality initiatives.

Qualifications

• Strong commercial experience as a Data Engineer within complex data environments.
• Solid knowledge of data modeling, ETL development, and analytics-ready data design.
• Strong proficiency in SQL and Python, with experience in scalable data processing.
• Hands-on experience with modern data platforms and lakehouse architectures.

Responsibilities

• Design and build reliable, scalable, and analytics-ready datasets and semantic models.
• Develop robust data models and ETL pipelines using SQL and Python or PySpark.
• Implement lakehouse and medallion architectures across ingestion, enrichment, and consumption layers.
• Establish multi-tenant data security, including row-level security within the semantic and BI layers.
• Optimize performance and costs through monitoring and targeted improvements.
• Work closely with data analysts and business stakeholders to translate data requirements into effective solutions.
• Contribute to data governance, data quality, lineage, and compliance initiatives.

Skills

Data engineering

Data modeling

ETL development

Analytics-ready data design

SQL

Python

Stakeholder communication

Dutch language (B-level)

Tools

PySpark

Lakehouse architectures

Job description

Harnham Eindhoven is seeking a Data Engineer to build analytics-ready datasets and semantic models, enabling scalable analytics across a large customer base. You will develop ETL pipelines using SQL and Python (or PySpark), implement lakehouse architectures, and ensure data security with multi-tenant and row-level controls.

Collaborate with analysts and stakeholders to translate requirements and drive data governance and quality initiatives.