Data Engineer

• Data Management: Design, develop, and maintain the data infrastructure that supports the Finance systems, ensuring data accuracy, integrity, and availability.
• Data Modeling: Apply data modeling techniques to design efficient and scalable data structures that support the Finance systems' reporting and analysis requirements.
• ETL Development: Utilize ETL tools like Informatica or extract, transform, and load data from various sources into the Finance systems, ensuring smooth and accurate data flow.
• Finance System Management: Collaborate with Finance stakeholders to understand their data requirements and ensure that the data infrastructure meets their needs for financial consolidation, regulatory reporting, cost allocation, and profitability reporting.
• Communication and Stakeholder Management: Strong communication skills to interact with various stakeholders, including senior management, technical teams, and business users.
• Data Mapping: Perform data mapping exercises to align data from diverse sources to the standardized OFSAA data model, ensuring data consistency and accuracy.
• Data Quality and Governance: Implement data quality and governance processes to maintain high data quality standards across the Finance systems.
• Performance Optimization: Identify and implement performance optimization techniques to ensure efficient data processing and reporting within the Finance systems.
• Integration: Collaborate with IT teams and external vendors to integrate new data sources and applications with the Finance systems.
• Regulatory Compliance: Thorough understanding of regulatory reporting requirements and compliance standards in the banking industry.
• AI/ML: Apply AI/ML for data classification, metadata inference, automated test‑case/document generation, and reconciliation efficiency.
• Agile Delivery: Works as part of cross‑functional Agile squads, contributing to sprint planning, refinement, and iterative delivery of data pipelines and finance systems enhancements.

Requirements:

• Minimum required experience is 5 years.
• Bachelor's degree in computer science, Information Technology, or a related field.
• Proven experience as a Data Engineer, handling Finance systems like OFSAA, Financial Consolidation, and Regulatory Reporting.
• Expertise in data modeling techniques and ETL tools (e.g., Informatica) to manage data integration and transformation processes.
• Knowledge of banking finance functions, including financial consolidation, cost allocation, and profitability reporting.
• Familiarity with big data technologies and their applications in data management and analysis.
• Understanding Hadoop architecture, tools like HDFS, Hive, Sqoop, Spark is critical for the tool.
• Proficiency in SQL and database management systems.
• Analytical mindset with a focus on data accuracy and attention to detail.
• Strong problem-solving skills and the ability to work independently as well as in a team environment.
• Strong knowledge of Agile delivery in banking/financial services.
• Proficiency with delivery/collaboration tooling (Jira/Azure DevOps, Confluence, Miro) and automated reporting (Power BI, Tableau).
• Familiarity with AI/ML concepts (basic model lifecycle, data quality, explainability, monitoring) and responsible AI considerations applied to data engineering.
• Awareness of data governance, privacy, cybersecurity, and regulatory expectations relevant to finance and regulatory data.