SC Cleared DATA Architect

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.

• 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-premises systems
• Evaluate and recommend new data technologies and platforms
• Provide technical leadership and mentoring to data engineering and analytics teams

• 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, Postgre
  
  SQL, MySQL
• Solid understanding of data warehouse and lakehouse architectures
• Experience with ETL/ELT and orchestration tools (e.g. 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

• Cloud data platforms (AWS, Azure, Google Cloud)
• Big data technologies (Hadoop, Spark, Kafka)
• UML/SysML
• API integration and microservices data flows