Data Architect

AlmavivA de Belgique; Amsterdam; Hybrid; EUR 90,000 - 140,000; Full time

Job summary

Almaviva de Belgique seeks a Senior Data Architect to lead enterprise data architecture, modelling, and platform integration. You will implement Lakehouse patterns and API-based data access while aligning with SAFe Agile practices.

You will design common data models, enforce governance, and collaborate with cross-functional teams to ensure data quality and scalable solutions across domains.

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 data architecture patterns (data Lakehouse, event-driven, API-based access).
• Familiarity with SAFe (Scaled Agile Framework).
• Excellent analytical and problem-solving skills with focus on data quality and technical debt.

Responsibilities

• Designs scalable and reusable data architectures for transversal use across domains and systems.
• Leads definition and standardization of enterprise-wide common data models (submissions, cases, products).
• Develops and enforces data governance policies for high-quality, compliant data usage.
• Oversees data model and metadata documentation for transparency and maintainability.
• Defines API contracts and ensures reusable data models for cross-team integration.
• Leads integration efforts with enterprise data platforms and data pipelines.

Skills

Data architecture

API design

Data governance

SAFe Agile

Stakeholder collaboration

Education

Bachelor's or Master's in CS/IS/Data Engineering

Job description

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.

• 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.
• 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