• Data Management and Analytics.
• Proficiency in Database types of mandatory (SQL & NoSQL).
• AI/ML Technologies/Software.
• Data Warehousing (ETL).
• Programming languages (Python, Java, C#).
• Big Data Tools/technologies like Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
• Statistical and data mining.

The principal accountabilities of this position are to:

• Identify data requirements and construct/extend data warehouse solutions, including Extract, Transform and Load (ETL) to meet business requirements by constructing mechanisms to acquire data from a range of sources with controls that deliver to required data quality standards.
• Build, Deploy, and Maintain AI/Machine learning models to support AI/ML Initiatives and models built for various business units.
• Develop and maintain scalable data pipelines and build out new API integrations to support continuing increases in data volume and complexity.
• Build and deliver solutions through appropriate coding practices that are robust and future-proofed to reduce waste and manage technology deficit and collaborate with all business units and relevant teams to develop a strategy for long-term data platform architecture.
• Collaborate with IT and business teams to improve data models that feed business intelligence tools.
• Build processes that support data transformation, workload management, data structures, dependency, and metadata to optimise data sets, data pipelines, and architectures.
• Test solutions in terms of the test plan and/or best practices and incorporate standard requirements – such as data quality control and future-proofing – into task definition and delivery.
• Provide third tier support, troubleshooting and problem resolution to systems in the Bank to restore availability within agreed service level agreement.
• Prevent recurrence of incidents by identifying and effectively responding to root causes through effective cause diagnosis and introducing system improvements.