Job Purpose Statement

Responsible for developing, maintaining, and optimizing financial data infrastructure. This role involves designing robust ETL/ELT pipelines, ensuring data quality for financial reporting and collaborating with finance stakeholders to drive data-driven insights.

Key Accountabilities

•  Develop dashboards and scorecards for performance monitoring using an array of tools including Power BI, OBIEE
•  Data Pipeline & Infrastructure Development: Lead the design and implementation of scalable data pipelines and warehouses to process complex financial data using tools like SQL Server, Azure Data Factory, ADLS, or AWS equivalents.
•  Financial Data Modeling: Build and maintain sophisticated data models, ETL procedures, and automated workflows to support financial reporting, regulatory compliance, and forecasting. Champion for a robust data architecture design.
•  Stakeholder Collaboration: Act as a bridge between technical teams and finance stakeholders (e.g., Accounting, FP&A) to define requirements and deliver actionable insights.
•  Data Governance & Quality: Ensure high data integrity, accuracy, and security of financial records. Implement data governance policies to adhere to compliance requirements.
•  Maintain technical documentation (data dictionary, lineage, pipeline runbooks) to support reuse and auditability.
•  Implement data validation, reconciliation and control frameworks
•  Perform any other duties as assigned.

• Degree in Finance, Commerce, IT, Data Science, or related discipline. (Finance Department exposure is a plus.)

• Strong SQL and data modeling; experience with ETL/ELT and data warehousing concepts.

• Programming for data (Python preferred) and orchestration/automation mindset.

• Ability to communicate with finance stakeholders and convert requirements into data products.

Education and experience

• 3–5 years in data engineering / analytics engineering, ideally supporting finance or enterprise reporting.

• 2-3 years experience in the Banking industry.