Senior Databricks Engineer

• Familiarity with GraphQL and schema-first APIs
• Experience with graph technologies (e.g., Neo4j)
• Affinity with or experience in AI / LLM-driven analytics or insights
• Familiarity with risk modeling, threat modeling, or frameworks such as MITRE ATT&CK
• Experience working with or strong affinity for security data domains (e.g., SAST, DAST, SCA, IaC, CSPM, vulnerability management such as CVEs/CVSS)

Gross monthly salary between € 5.030 and € 7.183 (scale 09).

• 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.

Are you interested into Cyber Security and willing to help developers to build safer solutions to be more secure against hackers? Join Tech4Dev and make a real impact on Rabobank's cybersecurity landscape. Read on or

• Pragmatic delivery mindset; focuses on delivering value quickly and iterating based on feedback
• Product-oriented thinking; treats datasets as products with users and adoption metrics
• Strong collaboration; aligns closely with DevOps and application engineers on shared pipelines and contracts
• Observability-first approach; ensures data flows are debuggable, transparent, and measurable
• Ownership mentality; accountable for data from source discovery to insight delivery

You will work closely with platform engineering and development teams, ensuring solutions are practical, secure, and user-friendly. Your contributions directly impact the efficiency and security of Rabobank's software delivery.

Senior Databricks Engineer

Develop innovative security platform to process reported quality and security findings of systems and with enrichment and connecting the data, creating more in-depth insights to improve the security posture view and faciliate the prioritization of risks.

• Implementing a large-scale data pipeline to ingest, aggregate and enrich findings reported by different tools and deliver prioritized actionable list of findings.
• Design practical and complex models to enable other analyst to use of the processed data.
• Ensure data quality and reliability
• Create insights and dashboards

• 36 hours per week
• Over 10 teams supported with platform solutions.
• 43,822 Rabobank colleagues worldwide

We believe in the power of differences. By combining the diversity of people, we become an even better bank. We are therefore curious about what you will add to our Tech4Dev team.

Tech4Dev develop and manage platform solutions that enable secure and efficient software development. Collaboration is our way of working; as one goal-oriented team within Rabobank. Our culture is characterised by openness, innovation, and a strong focus on continuous improvement.

For us, your development and that of society go hand in hand. That is 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 & the world around you at the same time".

You will see this reflected in your personal development budget, our hybrid working environment, and a good balance between work and home. You can work on banking matters for our private and business customers, but also on social issues such as food and energy transitions.

At Rabobank, we believe we become stronger by bringing together people who complement each other. By embracing our differences, we bring out the best in each other. We seek diversity in knowledge, skills, and experience, but also in gender, background, and culture. We strive for variety and the space to be yourself in every department - whoever you are. That is what diversity and inclusion at Rabobank is all about.

• Bachelor's or master's degree in computer science or a related field, demonstrating a solid theoretical foundation and analytical ability
• At least 4 years of relevant experience in data engineering, building and operating scalable data platforms in production environments
• Strong programming skills (Python) with software engineering best practices, including testing (unit/integration) and version control
• Solid experience with data engineering fundamentals: ingestion, transformation, serving, and building scalable, production-grade pipelines
• Experience designing data models for both analytics and operational use cases, including asset correlation and relationship-driven insights (e.g., graph-based approaches)
• Hands-on experience integrating multiple data sources (APIs, event streams, databases), including event-driven or asynchronous data flows
• Strong hands-on experience with Databricks (Delta Lake, Structured Streaming, Unity Catalog), including Medallion architecture, performance optimization, and operationalization via workflows and CI/CD (e.g., Terraform, Asset Bundles)
• Strong understanding of data quality, validation, observability, and reliability in production environments
• Comfortable working in containerized environments and modern DevOps ecosystems
• Ability to translate product needs into data logic, including prioritization and risk-based insights
• Striving for results (Resultaatgericht): You consistently pursue measurable outcomes and drive projects to completion
• Stimulating collaboration (Collaborating): You foster teamwork, encourage knowledge sharing, and build strong relationships across multidisciplinary teams

To ensure that we assess all candidates equally for suitability for this position, we do not require a mandatory cover letter. Instead, we ask all candidates the same three questions to see how your profile matches the role. Please pay sufficient attention to answering these questions and explaining your answers; together with your CV, these responses form the basis for our evaluation in this round. Submitting both a CV and answers to the three questions is the minimum requirement to be considered in the selection process. A cover letter is not mandatory but may be submitted optionally.

You may draw on your work experience, volunteer work, education, private life, and so on. Use a maximum of 200 words per question and provide no more than two examples. Below are the questions:

• Describe a complex data pipeline you designed and brought into production. What was your role?
• How have you used Databricks in a scalable production environment, including CI/CD, monitoring, and data quality?
• How would you correlate security findings from multiple sources and turn them into one prioritized list of risks?

Please submit these answers in the application section titled 'Add your cover letter (optional)' on the website portal.