Roles & Responsibilities:
- Define end-to-end architecture for the IFRS17 data platform with focus on scalability, auditability, and performance
- Lead modernization of legacy SSIS-based ETL systems to Azure Databricks Lakehouse architecture
- Design and implement Lakehouse architecture (Bronze, Silver, Gold layers) for ingestion, transformation, and serving
- Establish data modeling and transformation standards aligned with IFRS17 regulatory requirements
- Define migration strategy including refactoring approaches, sequencing, dependencies, and cutover planning
- Ensure reconciliation, validation, and functional parity between legacy and modern systems
- Design enterprise orchestration flows using Control-M and Azure Data Factory (ADF) integration
- Define retry mechanisms, failure handling, restartability, and operational resilience across pipelines
- Establish monitoring, alerting, dashboards, and runbooks for production stability
- Define coding standards for PySpark, SQL, and reusable data engineering frameworks
- Implement governance frameworks for logging, auditing, and regulatory compliance
- Define CI/CD, environment promotion strategy, and deployment best practices
- Drive non-functional requirements including performance optimization, scalability, cost efficiency, and DR/BCP
- Lead architecture reviews, design sign-offs, and enforce engineering standards
- Collaborate with finance, governance, security, and delivery stakeholders to align technical solutions with business needs
- Mentor technical teams and uplift engineering maturity across the organization
