Technical Lead - Data Engineer

Job Description:

• Bachelor's degree in Computer Science, IT, Engineering, or related field with 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 in the database engine, query optimisation, indexing strategies, and complex data retrieval and manipulation at scale.
• ETL Development: Proficient in designing and building robust, large-scale ETL pipelines using SSIS, including custom scripting with C# for advanced data manipulation tasks; experience with BIML for automated SSIS package generation is a strong advantage.
• Reporting & Visualisation: 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 modelling (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 artefacts.

Requirements:

Preferred qualifications:

• Experience with on‑premise data virtualization or logical data warehouse concepts.
• Understanding of data mesh or data fabric architecture patterns.
• Familiarity with Kubernetes, microservices architectures, or containerised data workloads in a hybrid environment.
• Metadata management and data lineage tools.
• Experience mentoring junior engineers or leading technical initiatives.
• Agile delivery methodologies and product‑oriented data architecture.

Other Professional Skills and Mind‑set:

• Autonomous Work Ethic – Work independently on complex problems while proactively seeking collaboration.
• Continuous Learning – Committed to staying current with data engineering trends and best practices.
• Analytical & Problem‑Solving – Approaches complex data and business challenges with structured thinking, sound judgement, and a pragmatic, solution‑oriented mindset.