Dev Ops Engineer

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

You & your role

Develop an innovative security platform to process reported quality and security findings of systems and, by enriching and connecting the data, create more in-depth insights to improve the security posture view and facilitate the prioritization of risks.

Examples for practice

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

Top responsibilities

• 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.

Together we achieve more than alone

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.

You & your talent

• Bachelor’s or master’s degree in computer science or a related field, demonstrating a solid theoretical foundation and analytical ability.
• Around 3–5 years of relevant experience in data engineering, working with data pipelines and platforms in production environments.
• Good programming skills (Python) and familiarity with software engineering practices such as testing and version control.
• Experience with core data engineering concepts: ingestion, transformation, and serving of data.
• Experience designing data models for analytics and/or operational use cases.
• Hands-on experience integrating multiple data sources (APIs, event streams, databases), with exposure to event-driven or asynchronous data flows.
• Experience working with Databricks (e.g., Delta Lake, Structured Streaming, Unity Catalog) and familiarity with data architecture patterns such as Medallion (bronze/silver/gold).
• Basic understanding of performance optimization and operating pipelines in production (e.g., workflows, monitoring, CI/CD).
• Understanding of data quality, validation, and observability concepts.
• Comfortable working in containerized environments and modern DevOps setups.
• Ability to translate functional or product requirements into data pipelines and insights.
• Eagerness to learn about prioritization and risk-based data insights.
• Striving for results (resultaatgericht): You work towards clear outcomes and are motivated to deliver value.
• Stimulating collaboration (Collaborating): You work well with others and are open to feedback and knowledge sharing.

Nice to have

• Familiarity with GraphQL and schema-first APIs.
• Exposure to graph-based data models or technologies (e.g., Neo4j).
• Interest in or experience with AI / LLM-driven analytics.
• Basic familiarity with risk modeling or threat modeling (e.g., MITRE ATT&CK).
• Interest in or exposure to security-related data domains (e.g., SAST, DAST, SCA, IaC, CSPM, vulnerability management such as CVEs/CVSS).