Senior Solution Architect – Data Governance & Generative AI

Shape the future of data governance and data marketplaces for more than 40 squads, enabling trusted and reusable data products for thousands of colleagues worldwide.

You & your role

Build a modern, federated and scalable data landscape where governance is embedded into platforms instead of added afterwards. As Senior Solution Architect, you translate enterprise data principles into practical architectures, standards and patterns that squads adopt in daily work. You operate at the heart of the Global Data & Analytics Platform and combine strategic architecture with hands-on technical design in complex, regulated environments.

Examples from practice

• Designing metadata, lineage and glossary architecture supporting both regulatory transparency and self-service discovery.
• Coaching squads to embed governance controls into pipelines, APIs and platform components.
• Defining guardrails so data context, quality and policy constraints are preserved in generative AI solutions.

Facts & figures

• You influence data governance and data platform architecture for more than 40 squads across 4 platform areas.
• Over 48,000 Rabobank colleagues worldwide.

Top 3 responsibilities

• Design enterprise-wide governance architecture for metadata, lineage, data quality, protection and AI-ready data foundations in a regulated environment.
• Guide squads from architectural principles to concrete implementations across cloud, on-premises and hybrid platforms.
• Connect governance, platform engineering and generative AI by shaping future-proof data and context foundations.

Design and evolve governance and data marketplace capabilities that improve discoverability, reuse and trust of data products, while supporting scalable platforms and responsible use of generative AI within Rabobank.

Together we achieve more than alone

“This is not an ivory-tower role, but architecture that engineers and product teams use every day.”

The teams are responsible for building and governing the Global Data & Analytics Platform. Collaboration is our way of working; as one expert and solution-oriented team within Rabobank.

You & your talent

We are especially interested in people who combine architecture with hands-on engineering experience.

• At least 7 years of experience in software engineering, platform engineering, data engineering, solution architecture, or a combination of these.
• At least 5 years of experience designing and implementing complex architectures in cloud, on-premises and hybrid environments.
• Solid hands-on experience with data governance, including metadata, lineage, data quality, policy implementation, data protection and operational governance patterns.
• Experience with data marketplace, data product discoverability, cataloguing and stewardship concepts.
• Strong familiarity with open-source data governance, metadata or platform technologies, and the ability to assess where open-source fits in an enterprise environment.
• Experience translating governance and compliance requirements into practical technical controls and platform designs.
• Understanding of context engineering, semantic modelling, metadata design, or related approaches that improve data usability for analytics, automation and AI.
• Experience with, or strong affinity for, generative AI architectures, especially where trusted enterprise data, retrieval, metadata, policy enforcement and explainability matter.
• Strong communication skills and the ability to work with engineers, architects, product owners, security specialists, data stewards and senior stakeholders.
• A pragmatic mindset: strategic when needed, but always grounded in implementation reality.

You stand out even more if you have:

• A background as a software engineer or platform engineer before moving into architecture.
• Experience with modern metadata ecosystems, knowledge models, developer platforms or internal data platforms.
• Familiarity with the Linux Foundation AI & Data landscape or comparable open ecosystems.
• Experience balancing enterprise governance needs with product team autonomy and developer experience.
• A strong point of view on how governance should be embedded into engineering workflows, not just oversight processes.
• Experience designing data and context foundations for generative AI, copilots, retrieval-augmented systems or intelligent agents.