1. Data Warehouse Architecture & Leadership • Lead the architectural design and implementation of the new Azure-based data warehouse. • Oversee the optimisation of the existing SSIS-based ETL environment during the transition phase. • Establish long-term data platform strategy in collaboration with BI and IT leadership.
2. Data Governance & Compliance • Own the data governance framework, ensuring standards for data quality, security, lineage, and access control are embedded in all solutions. • Partner with compliance and legal teams to meet regulatory requirements for data storage and processing. • Champion the use of data cataloguing and metadata management tools.
3. Collaboration & Stakeholder Engagement • Work directly with senior stakeholders across business units to translate needs into actionable technical solutions. • Serve as the primary point of contact between the BI team, engineering, and external vendors for data infrastructure matters. • Facilitate workshops, architectural reviews, and cross-team solution design sessions.
4. Technical Delivery & Mentorship • Lead the build, testing, and deployment of robust ETL/ELT pipelines for multi-source integration. • Ensure smooth migration of historical and real-time data to the new warehouse with minimal downtime. • Mentor and support junior and mid-level engineers in technical best practices and solution delivery.
5. Performance Monitoring & Continuous Improvement • Implement platform monitoring solutions to track and optimise performance. • Drive continuous improvement in architecture, tooling, and governance processes.
Education
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field.
Technical Experience
5+ years in data engineering, with experience in data warehouse design and development.
Strong hands-on experience with SSIS for ETL processes.
Proven expertise in Azure Data Platform components (Azure Data Factory, Azure Synapse Analytics, Azure SQL Database, Data Lake Storage).
Strong SQL skills (T-SQL preferred).
Experience implementing data governance principles, including data quality frameworks, security/access controls, and metadata management.
Experience with data modeling (Kimball/Star Schema/Snowflake).
Proficient in performance tuning and troubleshooting data processes.