(Senior) Data Engineer – ROP Data Platform

• Thirteenth month's salary and 8% holiday allowance

• 10% Employee Benefit Budget

• EUR 1,400 development budget per year

• Hybrid working: balance between home and office work (possible for most roles)

• A pension, for which you can set the maximum amount of your personal contribution

View all our benefits.

You ensure the smooth operation of ROP's Data Platform
 

As a Data Engineer in Data Loom, you design and build the data foundations that power platform-wide visibility. You work across a modern cloud-native stack (AWS and Databricks) and collaborate closely with the ROP platform teams that produce data, as well as internal Rabobank teams whose systems and data we integrate with.

You bring both engineering rigour and analytical instinct: you care about pipeline reliability as much as the insights that pipelines unlock.
 

You work as part of the Digital Platform - Backend & Creator Foundation department, together with 15+ contributing teams, around 120 developers, on the internal development platform: the Rabo Online Platform. The foundational services of the Rabo Online Platform facilitate the engineering journey for more than 160+ squads, spanning the entire Retail NL Rabobank and parts of Wholesale and FEC Tech.
Squad Data Loom is responsible for the ROP Data Platform, which contains the data and management insights for Rabo Online Platform’s services spanning across 15+ contributing teams.

We are essential in driving quality and adoption across the organisation and provide management reporting on the progress.

Our Tech Stack:

• AWS

• Databricks

• Python wheel files

• ETL pipelines on Azure DevOps

• Power BI dashboards

• 36 or 40 hours per week

• Reaching 9.5 million customers globally

• International environment with a focused group of highly skilled team members

• ROP Platform currently reaches 160+ squads, approx. 1,200–1,500 engineers

• Collaboration with 15+ contributing teams on the ROP platform

• Design, build, and maintain scalable data ingestion pipelines from ROP platform services into the Data Loom platform

• Package ETL pipelines into Python wheel files

• Develop transformation and enrichment logic to produce clean, reliable datasets for cross-platform insights

• Implement and manage data orchestration using Databricks and AWS storage solutions

• Monitor pipeline health, build alerting, and maintain data quality standards across the platform

• Contribute to the design of the Data Loom data model, ensuring it is scalable, governed, and aligned with Rabobank's enterprise data standards

We believe in the power of differences. By combining people's differences, we become an even better bank. We are curious about what you will bring to our team Data Loom in area Backend and Creator Foundation. The team is responsible for managing and improving data management for the Rabo Online Platform, our Internal Development Platform.
Collaboration is our way of working, increasing the value of our data for Rabobank by improving its quality and reliability to support standardization and simplification.

For us, your development and that of society go hand in hand. That’s why we want to invest in you and work together for a better world. We summarise this in one sentence: ‘At Rabobank, you work on yourself and the world around you at the same time. You’ll see this reflected in your personal development budget, our hybrid working environment, and a healthy balance between work and home. You can work on banking services for our private and business customers, as well as societal issues such as food and energy transitions.

At Rabobank, we believe we become stronger through people who complement each other. By embracing our differences, we bring out the best in one another. We seek diversity in areas such as knowledge, skills, and experience, but also in gender, background, and culture. Across every department, we strive for variety and the freedom to be yourself – whoever you are. That’s what diversity and inclusion at Rabobank is all about

Essential:

• 3–6 years of hands-on experience as a Data Engineer in a professional setting

• Proven experience with the data engineering fundamentals: ingestion, transformation, and serving of data

• Proven experience building and operating ETL pipelines

• Working experience with Databricks or the Delta Lake / Lakehouse paradigm

• Strong Python and SQL skills; comfortable with PySpark for large-scale transformations

• Ability to design reliable, observable, and maintainable data pipelines — not just build them

• Experience working in cross-functional, agile teams; ability to translate between engineers and non-technical stakeholders

• Familiarity with data governance concepts — lineage, quality checks, access control

Advantageous

• Exposure to data lineage tooling

• Familiarity with internal developer platforms, platform engineering, or developer tooling contexts

• Understanding of enterprise data integration patterns (event-driven ingestion, CDC, API-based extraction)

• Experience with exposing data via APIs using GraphQL

• Experience working within a regulated financial services environment

• Affinity with or experience in AI / LLM-driven analytics or insights

Who you are

• You take end-to-end ownership: you care about what happens to data after it leaves your pipeline

• You are a collaborative engineer — comfortable working directly with platform service teams to agree on data contracts and schemas

• You communicate clearly with team members, engineers and non-technical stakeholders in the guidance teams. You are comfortable representing your point of view and expertise

• You are pragmatic: you favour working solutions over perfect ones, and you iterate