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# Data Products & AI Architect - Enterprise Applications, FinTech

- **Company:** Booking.com
- **Location:** Amsterdam, Netherlands
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Airflow, Amazon Web Services, Audit Trail, Microsoft Azure, BigQuery, Code Review, Data Architecture, Information Engineering, Data Governance, Data Retention, PCI Data Security Standards, Role-Based Access Control, OpenAI, SAP (Applications), Enterprise Data Management, Enterprise Software Applications, Great Expectations (Foster Youth College-readiness and Support Program), Large Language Models, Snowflake, Apache Spark, AI Platforms, Collibra, Apache Kafka, Terraform, Automation Anywhere, Databricks
- **Published:** October 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f17b9a08e81af8cc

## About the Role

* 10+ years in data engineering or data architecture, with at least 3-5 years in a lead or architect role owning platform design for large organisations
 * Delivered at least one enterprise data or AI platform into supported production (with SLAs, on-call and real internal users), using tools like Snowflake, Databricks, BigQuery, Spark, Kafka or Airflow. For example, you've migrated a legacy warehouse to a modern lakehouse, or launched a self-serve data platform used by multiple teams
 * Experience building AI applications or agents that run in production, not just prototypes. You've worked with LLM APIs (e.g. OpenAI, Anthropic, AWS Bedrock, Vertex AI) and frameworks like LangChain, LangGraph or MCP
 * Hands-on data architecture skills across semantic modelling (e.g. dbt, LookML, Cube), data contracts, data quality (e.g. Great Expectations, Soda, Monte Carlo), lineage (e.g. OpenLineage, DataHub, Collibra, Unity Catalog) and access controls (RBAC/ABAC, row- and column-level security).
 * Designed systems that run at high volume, for example processing billions of events or terabytes of data per day
 * Practical experience with security, privacy, governance and audit requirements for enterprise data and AI, such as GDPR, SOX, PCI DSS, ISO 27001 or the EU AI Act. You've built in controls like encryption, PII masking, audit logging and data retention, and supported internal or external audits
 * A track record of working with Product, Engineering and Finance stakeholders. You can point to times you turned unclear requirements into a clear technical plan, explained trade-offs (cost vs. speed vs. risk) to non-technical audiences, and got teams aligned on a decision, for example through architecture decision records (ADRs) or design reviews.

Nice to have

 * Experience in FinTech, payments or other regulated industries
 * Experience with infrastructure as code (e.g. Terraform) on AWS, GCP or Azure
 * Certifications such as AWS/GCP Professional Architect or Databricks/Snowflake architect

## Description

As our Data & AI Architect, you will lead technical design for these capabilities and work hands-on with engineering teams to bring them into production. You will connect data products, semantic models, enterprise systems and AI services into solutions that are reliable, traceable and practical to operate. Your designs will support shared capabilities across brands while respecting local business definitions, systems and data-access boundaries.

You will partner closely with the AI First Finance Product leaders, engineering leaders, Finance experts, enterprise data teams and Central Technology. Together, you will translate prioritized business problems into achievable delivery increments, making trade-offs between speed, quality, cost and risk explicit. You will validate critical decisions through working implementations and production evidence, and develop reusable patterns that help subsequent teams deliver faster., * Partner with Product, Engineering, Finance, Data Governance, Legal, Security, and Compliance to translate business priorities and governance policies into scalable architecture, balancing value, delivery speed, cost, and risk.

 * Connect AI products to certified Finance data with clear definitions, data contracts, quality standards, lineage, and access controls.
 * Design Finance intelligence with governed calculations, traceable answers, and evaluation against examples validated by Finance.
 * Design and deploy AI workflows with secure integrations, robust SAP and third-party application connections, appropriate permissions, human approvals, and safe failure handling.
 * Reuse, extend, and evaluate enterprise capabilities, making clear build, buy, and reuse decisions in collaboration with Central Technology.
 * Validate architecture through prototypes, reference implementations, code reviews, process automation, and hands-on support for production delivery.
 * Embed evaluation, monitoring, audit evidence, SOX compliance, and segregation of duties (SoD) risk controls throughout the AI lifecycle alongside Engineering, Security, and Risk & Controls.
 * Architect robust compliance structures and reusable patterns across teams and brands that scale with company growth while respecting local business definitions and data boundaries.
 * Measure quality, reliability, performance, cost, and reuse to guide continuous improvements with Product and Engineering.