Data Engineer (MSSQL, SSIS) #IAC
Recruit Express Pte Ltd · Singapore, Singapore ·
- Category
- Data engineering
- Experience
- 7+ years
Design, build, and maintain SQL Server databases and SSIS-based ETL pipelines for a Singapore client, including performance tuning, data-quality controls, job monitoring, and production support. Requires 7+ years of hands-on experience with MSSQL, T-SQL, and SSIS.
Key Responsibilities:
- Design, develop and maintain 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.
- Work closely 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.
- Any other ad-hoc duties as assigned by supervisor.
Required Skills and Qualifications:
- At least 7 years of relevant experience in database development, data engineering or data integration.
- Strong hands-on experience with Microsoft SQL Server.
- Strong hands-on experience developing and supporting SSIS packages.
- Advanced knowledge of SQL and T-SQL.
- Experience with stored procedures, functions, views, triggers and SQL Server Agent jobs.
- Strong understanding of ETL design and data-integration principles.
- Experience with query optimisation, indexing and database performance tuning.
- Experience handling large data volumes and complex data transformations.
- Experience troubleshooting failed jobs, data issues and production incidents.
- Good understanding of data quality, reconciliation and validation controls.
- Experience working across development, testing and production environments.