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- Solid hands-on experience with Microsoft Technology Stack (2022)
- Extensive experience of SQL/ data warehousing
- Proven experience of data engineering activities such as release management, environment controls, CICD pipeline orchestration
- Experience working with Python and Power BI
- Proven ability of Microsoft BI software development including database / reporting development, full development cycle
- Strong data modelling, problem solving, information analysis, attention to detail, flexibility of approach
- The ability to deal directly with business functions and interpret their thoughts into successful data & analytics solutions
- The ability to design and develop complex BI/MI solutions in line with agreed architectural principles and toolsets
- Capable of working closely with the business and delivering complex requirements to tight timescales
- Strong interest in latest data engineering technologies, best practices, techniques and trends in the data industry
Required Toolsets:
- Kimball data modelling
- Microsoft SQL Server
- Python, MDX, DAX
Responsibilities
The Data Manager will be responsible for supporting the Head of Data and Analytics and the wider business to build and deliver components of an enterprise data management platform for WRBU, utilizing Microsoft Technology stack for data ingestion, transformation & storage, and Power BI for analytics and reporting. The role includes:
- Data Support: Acting as a Subject Matter Expert in Data, managing ETL/ELT pipelines, peer/code reviews, ensuring data integrity and accuracy.
- Data Warehousing: Managing data warehousing solutions, designing and developing ETL/ELT processes, data lakes, data marts, reports, and dashboards.
- MI Development and Maintenance: Developing and maintaining Management Information, gathering requirements, developing reports, and supporting their deployment.
- Data Validation: Developing validation checks for data entry based on business rules, ensuring compliance with Solvency II, Sox, and business needs.
- Data Governance: Supporting data governance policies, managing data in line with regulatory requirements, and ensuring transparency of progress.
- Market Messages: Processing market messages and resolving issues efficiently.
- MI Projects: Reviewing project requirements, developing data solutions, and supporting project lifecycle activities.