Technical Lead - Data Engineer

. 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

o SQL Server (2017, 2019, 2022): Deep expertise inthe database engine, query optimisation, indexing strategies, and complex dataretrieval and manipulation at scale.

o 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.

o 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.

o SSAS & Analytical Modelling: Strong expertise in SSAS Tabular model development proficient in DAX and MDX for complex analytical calculations and KPI modelling.

o 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.

o 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.

o 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.

o 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.