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GDPR Data Architect

BrightBox Group
Glasgow, City Of Glasgow, G2 1AL, United Kingdom
Last month
£600 – £700 pd
Applications closed

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Posted
23 Mar 2026 (Last month)
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Data Architect

6 month contract

Glasgow 2-3 days per week

£700 per day

We are seeking an experienced Data Architect who can define, govern, and deliver GDPR compliant enterprise data architectures across relational (Oracle), NoSQL, unstructured data platforms, and Data Warehouse. The ideal candidate will possess strong expertise in data integration, migration, and centralisation initiatives, ensuring privacy by design across complex, distributed data landscapes.

Key Responsibilities:

Data Architecture & Modelling:

- Define enterprise data architecture aligned with GDPR and organisational data strategy.

- Design conceptual, logical, and physical data models for relational databases (e.g., Oracle), NoSQL databases (e.g., MongoDB), and unstructured data.

- Establish standards for data classification, metadata, and ownership across structured and unstructured data.

- Ensure data models support traceability, lineage, and regulatory reporting.

Data Governance:

- Architect privacy by design and privacy by default solutions.

- Define data retention, archival, anonymization, and deletion strategies across all data stores.

- Design architectures supporting DSAR, right to erasure, and consent management.

- Define security architecture including role-based access control (RBAC), column/row level security, data masking, tokenization, and encryption.

- Ensure compliance across cloud, hybrid, and on-premises environments.

GDPR & Regulatory Compliance:

- Architect solutions fully aligned to GDPR and applicable regulatory frameworks.

- Implement and operationalize key compliance capabilities: data retention & archival policies, right to erasure/data subject rights, data minimization, security & access controls, auditability, traceability & data lineage.

- Work with Risk and Compliance teams to translate regulatory needs into technical design.

Data Integration & Enterprise Connectivity:

- Design and govern enterprise data integration architectures using ETL/ELT frameworks, API-based integration, event-driven and streaming integration, message queues and middleware.

- Define integration patterns for real-time, near real-time, and batch processing.

- Ensure consistent data movement while preserving lineage, quality, and compliance.

Data Migration & Centralisation:

- Lead data migration initiatives from legacy and distributed systems to centralised platforms such as enterprise data warehouses, data lakes, and MDM.

- Define migration strategies including data profiling and cleansing, PII identification and remediation, and incremental and phased migrations.

- Ensure minimal business disruption and full GDPR compliance during migration.

- Validate post-migration data quality, security, and accessibility.

Collaboration & Oversight:

- Provide architectural leadership and guidance to Data Engineers and Platform teams.

- Work closely with Legal, Compliance, Security, and Risk teams.

- Support GDPR audits, regulatory assessments, and architectural reviews.

- Define and maintain architecture standards, patterns, and documentation.

Required Skills & Experience:

- 15+ years of overall IT experience, with at least 5+ years of hands-on experience in enterprise data architecture, design, governance, and implementation.

- Strong experience designing and implementing enterprise-grade ETL/ELT data pipelines. Hands-on experience with tools such as SQL, NoSQL Datastores, Talend, Informatica, IBM DataStage, or equivalent platforms, Collibra, Data Lineage, Alfresco.

- Proven experience acting as an enterprise or lead data architect within a large, multinational organisation across the disciplines of metadata management, data quality, data warehousing, reporting & analytics, and data governance.

- Strong knowledge of data modelling techniques (conceptual, logical, and physical).

- Excellent communication and stakeholder management skills.

- Solid understanding of SDLC methodologies including Agile, DevOps, rapid prototyping, and iterative delivery models.

- Ability to assess and estimate the financial impact of technology decisions.

- Capability to evaluate emerging technologies and understand their impact on business models

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