Finance Data Analytics Engineer

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. Qualifications 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.