Technical Lead - Data Engineer

Main responsibilities Main responsibilities of the role: Lead hands-on design and development of end-to-end Microsoft BI solutions - including ETL pipelines (SSIS), semantic models (SSAS Tabular), and reporting layers (SSRS, Power BI) — across multiple banking domains Translate business requirements into technical solutions by working closely with Business Analysts and business stakeholders across the bank, ensuring delivered solutions are fit-for-purpose, accurate, and aligned to business intent. Optimise SQL and data model performance through advanced query tuning, indexing strategies, and dimensional modelling best practices on SQL Server (2017, 2022), ensuring solutions meet enterprise-grade performance and reliability standards. Set and enforce development standards through code reviews, technical governance, and adherence to configuration management and SDLC/Agile practices, maintaining consistently high delivery quality across the team. Mentor and guide junior and mid-level engineers, providing hands-on technical support, knowledge sharing, and fostering a culture of engineering excellence within the Data & Analytics team. Collaborate with Infrastructure and Platform teams on environment provisioning, SQL Server configurations, performance tuning, CI/CD pipeline setup, and hybrid cloud deployments to ensure reliable and scalable delivery. Create and present technical diagrams — including data architecture, integration flows, and system context diagrams — to communicate solution designs effectively to both technical and non-technical audiences. Drive innovation and continuous improvement by evaluating emerging tools and technologies, building Proof of Concepts (POCs), and presenting findings and recommendations to senior stakeholders. Collaborate with Data Scientists, Business Analysts, and stakeholders to deliver datasets aligned with operational and analytical needs. Provide L3 support for the applications in scope and expert consultation for complex data challenges; evaluate and recommend new tools and practices to improve agility and performance. Qualifications and Profile Experience Bachelor's degree in Computer Science, IT, Engineering, or related field with demonstrated continuous learning ethics. 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 …