We are seeking two experienced SC Cleared Data Architects (Level 6) to support the design, delivery, and governance of data-intensive systems for a major programme based in Edinburgh.
You will be responsible for defining and implementing enterprise-grade data architectures that ensure data is accurate, secure, accessible, and aligned to business objectives. This role requires hands-on experience across the full delivery life cycle, from requirements gathering and solution design through to implementation and handover.
You will work proactively with IT teams, data engineers, system engineers, and business stakeholders, playing a key role in shaping data models, data flows, and governance frameworks across cloud and on-prem environments.
Key Responsibilities
Design and implement enterprise-level data architectures, including databases, data warehouses, and data lakes
Develop and maintain conceptual, logical, and physical data models
Define and enforce data management standards, policies, and best practices
Collaborate with data engineers to design and optimise ETL/ELT pipelines
Ensure data quality, consistency, security, and compliance across platforms
Translate business data requirements into scalable technical solutions
Support data governance initiatives, including metadata management and MDM
Oversee data integration across cloud and on-premise systems
Evaluate and recommend new data technologies and platforms
Provide technical leadership and mentoring to data engineering and analytics teams
Essential Skills & Experience
Bachelor's degree in STEM, Computer Science, Data Science, or related field (Master's preferred)
Strong experience in data architecture, database design, or data engineering
Excellent SQL skills and experience with databases such as Oracle, SQL Server, PostgreSQL, MySQL
Solid understanding of data warehouse and lakehouse architectures
Experience with ETL/ELT and orchestration tools (eg Informatica, Talend, Apache Airflow)
Proven experience designing data models
Strong understanding of data governance and data security requirements
Excellent communication, documentation, and problem-solving skills
Exposure to AI/ML data pipelines and analytics platforms
Desirable Experience
Cloud data platforms (AWS, Azure, Google Cloud)
Big data technologies (Hadoop, Spark, Kafka)
UML/SysML
API integration and microservices data flows