Technical Lead - Data Engineer

Main responsibilities • 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 using Azure DevOps or equivalent tooling, including automated testing and release management for BI artefacts. 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 manageme #J-18808-Ljbffr