(Senior) Data Engineer - ROP Data Platform
Role details
Job location
Tech stack
Job description
- Salary: Gross monthly salary between EUR 5,030 and EUR 7,183 (scale 09) for a 36-hour work week.
- Extras: a thirteenth month, 8% holiday allowance, and a 10% Employee Benefit Budget.
- Development budget: EUR 1,400 development budget per year for your growth and development.
- Hybrid working: a balance between home and office work (possible for most roles).
- Pension: decide for yourself the amount of your personal contribution.
Or 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 & your role
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
Facts & figures
- 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
Top responsibilities
- 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
Requirements
- 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