Job Description:
AI Data Architect (AI Data Foundations)
Location - Erskine, London, Farnborough or Newcastle
Candidates are required to be eligible for clearance
We are seeking an AI Data Architect to design and implement AI-ready data foundations. You will define data models, storage patterns, pipelines, and governance frameworks that support machine learning and analytics. Working closely with data engineers and ML engineers, you will ensure data is well-structured, accessible, secure, and scalable for AI use cases.
Key Responsibilities
1. Design and maintain data models and schemas (relational, graph, time-series) aligned to AI and business needs.
2. Define scalable data storage architectures across databases, data lakes, and warehouses in cloud environments.
3. Build and oversee ETL/ELT pipelines to integrate batch and streaming data from multiple sources.
4. Establish data governance, quality, security, privacy, and compliance standards.
5. Implement metadata management and data lineage for transparency and traceability.
6. Collaborate with data, ML, and analytics teams to deliver AI-ready datasets and features.
7. Monitor, optimise, and scale data platforms for performance, cost efficiency, and growth.
Required Qualifications
8. Bachelor’s degree in Computer Science, Information Systems, or related field (or equivalent experience).
9. Previous experience in data architecture, data engineering, or similar roles.
10. Strong data modelling and database design skills (SQL, relational, and NoSQL databases).
11. Hands-on experience building and managing data pipelines (ETL/ELT) using Python, SQL, or related tools.
12. Experience with cloud-based data platforms and modern data architectures.
13. Solid understanding of data governance, quality management, security, and privacy.
14. Strong communication skills and ability to collaborate across technical teams.
Preferred Experience
15. Experience supporting AI/ML or advanced analytics projects.
16. Familiarity with data catalogues, governance, and lineage tools (e.g. Collibra, Alation, Atlas).
17. Exposure to ontologies, semantic modelling, or knowledge graphs.
18. Experience with modern architectures (lakehouse, data mesh, streaming/event-driven systems).
19. Relevant cloud or data architecture certifications.
At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.