The IT Data Management and Analytics Manager will be responsible for managing and maintaining the company's data infrastructure, including databases, data warehouses, and data lakes, to ensure scalability, flexibility, and resilience. The incumbent will also be responsible for data consumption layers such as analytics as well as ensuring the accuracy, completeness, and reliability of data used in business decision-making processes.
1. Implement and operationalize data management policies and procedures to ensure data consistency, quality, and accuracy across the bank's systems and applications.
2. Collaborate with business units to understand their data needs and provide solutions that meet those needs, while also aligning with the bank's overall data strategy.
3. Manage and oversee the bank’s data analytics capabilities, including data visualization, predictive analytics, and machine learning, to support the bank's business objectives.
4. Implement and operationalize the data quality and data governance processes that promote data consistency, quality, and accuracy across the bank's systems and applications.
5. Develop and implement a data integration and data warehousing strategy that supports the bank's business objectives and enables effective data management and analytics.
6. Develop and maintain the data modelling strategy ensuring alignment with the bank's data strategy and supports the bank's business objectives.
7. Manage and maintain the company's data infrastructure, including databases, data warehouses, and data lakes, to ensure scalability, flexibility, and resilience.
8. Develop and manage a team of data analysts, data scientists, and data engineers to support the bank's data management and analytics capabilities.
9. Stay up to date with emerging technologies and trends in data management and analytics to ensure the bank's data capabilities remain competitive and innovative.
- Bachelor’s degree in computer science, Information Technology, or a related field.
- 10+ years of experience in data management and analytics.
- Strong understanding of data warehousing, data modeling, and data integration concepts.
- Experience with data visualization tools such as Power BI.
- Experience with data analytics tools such as R, Python, or SAS.
- Experience with MS-SSAS and MS-SSIS is a plus.
- Strong leadership and communication skills.
- Ability to work collaboratively with cross-functional teams.
- Strong problem-solving and critical thinking skills.