Location: Glasgow | Hybrid – 2–3 days onsite
Rate: Up to £410/day Inside IR35
Contract until 31 December 2026 (renewable)
We’re looking for an experienced SQL Server Lead to join a major financial services environment, supporting the design, development and optimisation of data warehouse and data distribution platforms across security, risk, controls and records management.
Key Responsibilities
- Lead end-to-end delivery of SQL Server components from technical design through to deployment and documentation.
- Develop and optimise complex T-SQL, including stored procedures, functions, views and data models.
- Own SQL Server performance tuning, including execution plans, indexing, partitioning, statistics and CPU/I/O optimisation.
- Build resilient batch and near-real-time data processing solutions.
- Implement testing, data quality checks and reconciliations for trusted reporting.
- Support production services, incident/problem management and root-cause analysis.
- Ensure database solutions meet security, access control, audit and records-management requirements.
- Work closely with analysts, engineers, architects and risk/governance stakeholders.
- Provide technical leadership through code reviews, engineering standards and mentoring.
Essential Skills
- Expert-level T-SQL / SQL Server development.
- Strong SQL Server performance engineering and troubleshooting experience.
- Excellent understanding of relational database principles and data modelling.
- Experience with database testing, automation and data quality controls.
- Strong understanding of secure database development, access management and auditing.
- Excellent communication and stakeholder management skills.
- Strong problem-solving and ability to manage complex workloads.
Desirable
- Git/GitLab, branching strategies and pull requests.
- CI/CD and database release automation.
- Nexus or similar artefact repositories.
- PowerShell, Linux shell scripting and/or Python.
- Data governance and records-management experience.
- Java and/or Scala, particularly alongside Spark-based processing
