Senior Data Architect (Hybrid) - Deadline 24/08/26

• Professional qualifications Bachelor's or master's degree in computer science, Information Systems, Data Engineering or a related field.
• Proven experience as a Data Architect or in a similar role focused on enterprise data architecture, data modelling, and platform integration.
• Solid understanding of modern data architecture patterns, including data Lakehouse, event-driven architectures, and API-based data access.
• Familiarity with Agile development methodologies, particularly SAFe (Scaled Agile Framework).
• Excellent analytical and problem-solving skills with a proactive mindset toward resolving technical debt and ensuring data quality.
• Effective communication and collaboration skills, with the ability to work closely with cross-functional technical and business teams.
• Role specific experience Extensive experience designing and maintaining common data models across large-scale enterprise systems (e.g., submissions, cases, products).
• Experience implementing data governance frameworks, retention policies, and classification schemes.
• Strong background in API design and the definition of clear and reusable API contracts between systems.
• Proven experience integrating data systems with external platforms, data hubs, and pipelines.
• Experience with testing frameworks for data, including generating and managing synthetic or representative test data.
• Demonstrated ability to assess, document, and resolve technical debt in data pipelines and data models.
• Experience with metadata management, data cataloguing tools, and improving data discoverability and reusability.

Data Architecture & Governance

• Designs scalable and reusable data architectures to support transversal use across multiple domains and systems.
• Leads the definition and standardization of enterprise-wide common data models (submissions, cases, products, etc.).

Topic Description

• Develops and enforces data governance policies to support consistent, high-quality, and compliant data usage.
• Oversees the documentation of data models and metadata to ensure transparency, alignment, and maintainability.
• Oversees the selection of data storage solutions and ensures appropriate means are selected based on the data categorization.

Data Quality, Classification & Retention

• Establishes data quality controls, validation frameworks, and monitoring mechanisms across key datasets.
• Defines and implements data classification standards and integrates them into data cataloguing solutions.
• Supports the implementation and enforcement of data retention and lifecycle policies in alignment with regulatory and business needs.

API Design & Integration

• Defines API contracts and facilitates alignment between producers and consumers of data services.
• Ensures APIs reflect well-defined and reusable data models, enabling efficient integration across teams and systems.
• Leads integration efforts with enterprise data platforms, ensuring data flows are secure, traceable, and optimised.

Testing, Documentation & Support

• Designs test data strategies for validating data pipelines and ensuring robustness of data-dependent applications.
• Supports, suggests and applies methods for the creation of synthetic data for testing purposes.
• Ensures technical documentation of data models, data flows, and integration points is maintained and accessible.
• Supports platform teams and domain owners by advising on best practices in using shared data assets and APIs.

Technical Design and Implementation

• Translates business and platform needs into scalable, secure, and maintainable data architecture designs.
• Supports resolution of legacy data issues, including schema harmonization, normalization, and versioning.
• Ensures alignment between data design and overall platform architecture, performance goals, and scalability needs.

Security, Compliance & Risk Management

• Ensures data solutions adhere to security and compliance standards, including data privacy, access control, and regulatory requirements.
• Collaborates with data protection and legal teams to ensure the architecture supports compliance-by-design principles.

Agile Collaboration & Continuous Improvement

• Actively participates in SAFe Agile ceremonies, supporting backlog refinement, planning, and reviews.
• Works with cross-functional teams including developers, analysts, and product owners to deliver fit-for-purpose data solutions and enforce established principles and governance.

Topic Description

• Continuously improves data architecture in response to feedback, evolving requirements, and new technology opportunities.

Level: Senior

• Delivery mode: Hybrid 20 days onsite (Amsterdam) and 200 days remote from Europe
• only EU Citizens can apply
• we will need a detailed Europass CV