Data Engineer (MSSQL, SSIS) – Contract

About the role

We are looking for an experienced Data Engineer on a contract basis to design, develop and maintain SQL Server databases and ETL solutions. The role involves building reliable data pipelines, optimizing queries and ensuring data quality for our business users.

Key responsibilities

• Design, develop and maintain Microsoft SQL Server databases and data solutions.
• Develop, enhance and support SSIS packages for data extraction, transformation and loading.
• Build reliable ETL processes across multiple source and target systems.
• Write and optimise complex SQL queries, stored procedures, functions and views.
• Analyse and improve database and ETL performance.
• Monitor scheduled jobs, interfaces and data‑processing activities.
• Investigate and resolve data‑quality, reconciliation and production issues.
• Develop controls for data completeness, accuracy and integrity.
• Support data migration, system integration and reporting initiatives.
• Maintain technical documentation, data mappings and operational procedures.
• Collaborate with business users to understand data and reporting requirements.
• Coordinate with application, infrastructure, security and vendor teams.
• Support production releases, incident management and root‑cause analysis.
• Ensure solutions follow security, access‑control and change‑management standards.
• Provide technical guidance and support to junior team members.

Required profile

• At least 7 years of experience in database development, data engineering or data integration.
• Strong hands‑on experience with Microsoft SQL Server and SSIS.
• Advanced knowledge of SQL and T‑SQL, including stored procedures, functions, views and triggers.
• Experience with query optimisation, indexing and database performance tuning.
• Proven ability to handle large data volumes and complex transformations.

Required skills

• Microsoft SQL Server
• SSIS
• SQL
• T‑SQL
• Stored procedures
• Functions
• Views
• Triggers
• SQL Server Agent
• ETL design
• Query optimisation
• Indexing
• Database performance tuning
• Large data volume handling
• Data quality controls