Senior Data Engineer (Databricks) — Hybrid Cloud

Harnham; Amsterdam; Hybrid; EUR 72,000 - 88,000; Full time

Benefits offered by this job

Hybrid work in Amsterdam

Salary around €80,000

Performance bonus

Learning and development budget

Job summary

Harnham, a well-established retailer, seeks a Senior Data Engineer to design, build and optimise scalable data solutions across the business from Amsterdam. This role shapes a modern data platform powering data-driven decisions for customer and commercial outcomes.

You'll work with Data Analysts, Data Scientists and product teams, implement cloud data warehouses on Azure/AWS/GCP, develop robust ETL/ELT pipelines, ensure data quality and governance, and mentor colleagues within the data function.

Qualifications

• Extensive commercial experience as a Data Engineer or Senior Data Engineer.
• Strong SQL and Python expertise.
• Experience with cloud data platforms (Azure, AWS, or GCP) and data warehousing.

Responsibilities

• Designing and developing robust data pipelines for batch and real-time data processing.
• Building and maintaining cloud data platforms and data warehouses.
• Supporting analytics, reporting, and ML initiatives.
• Improving data quality, governance, monitoring, and observability across the platform.
• Collaborating with Analysts, Scientists, Product teams and stakeholders.
• Driving best practice in data engineering, architecture, and platform performance.
• Mentoring colleagues within the data team and identifying automation opportunities.

Skills

SQL

Python

Cloud data platforms

Data modelling

ETL/ELT

Airflow

Data architecture

Stakeholder management

Collaboration

Continuous improvement

Tools

Airflow

Job description

Harnham, a well-established retailer, seeks a Senior Data Engineer to design, build and optimise scalable data solutions across the business from Amsterdam. This role shapes a modern data platform powering data-driven decisions for customer and commercial outcomes.

You'll work with Data Analysts, Data Scientists and product teams, implement cloud data warehouses on Azure/AWS/GCP, develop robust ETL/ELT pipelines, ensure data quality and governance, and mentor colleagues within the data function.