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.