Technical Lead - Data Engineer

Core qualifications

• Bachelor's degree in Computer Science, IT, Engineering, or a related field with a demonstrated continuous learning ethos.
• Minimum 10 years of hands-on experience in the design, development, and maintenance of large-scale Microsoft BI solutions in enterprise environments, ideally within banking, financial services, or a similarly regulated industry.
• Proven experience delivering end-to-end BI solutions from requirements gathering through to production support, across multiple concurrent business domains.
• Demonstrated experience in a technical lead or senior individual contributor capacity, including solution design ownership, code reviews, and team mentoring.
• Solid understanding of SDLC and/or Agile/Scrum development frameworks and methodologies.

Must-have qualifications

• SQL Server (2017, 2019, 2022): Deep expertise inthe database engine, query optimisation, indexing strategies, and complex dataretrieval and manipulation at scale.
• ETL Development: Proficient in designing andbuilding robust, large-scale ETL pipelines using SSIS, including customscripting with C# for advanced data manipulation tasks; experience with BIMLfor automated SSIS package generation is a strong advantage.
• Reporting & Visualization: Hands-on experience developing enterprise reports and dashboards using SSRS and Power BI, including Power BI Service, row-level security, and deployment pipelines.
• SSAS & Analytical Modelling: Strong expertise in SSAS Tabular model development; proficient in DAX and MDX for complex analytical calculations and KPI modelling.
• Data Warehousing & Architecture: Strong command of data warehouse design principles, including dimensional modeling (star/snowflake schemas), data marts, slowly changing dimensions, and data lineage—with experience maintaining and evolving large-scale DWH environments.
• Open-Source Data Pipelines: Hands-on experience building and maintaining data pipelines using open-source frameworks such as Apache Airflow, Apache Spark / PySpark, or dbt, complementing the core Microsoft BI stack.
• Broader Database & DWH Platforms: Working experience with non-Microsoft database and DWH platforms such as PostgreSQL, MySQL, Snowflake, Amazon Redshift, or Google BigQuery, demonstrating versatility across data ecosystems.
• CI/CD & DevOps: Experience implementing Continuous Integration/Continuous Deployment pipelines using Azure DevOps or equivalent tooling, including automated testing and release management for BI artifacts.