Define the enterprise data engineering architecture and technology standards across DB2, SQL Server, IBM DataStage, IBM Workload Scheduler, Oracle GoldenGate, and AWS
Lead the multi-year platform modernization roadmap — phased migration from legacy on-premises patterns to cloud-native AWS data engineering patterns
Govern platform health including capacity planning, performance benchmarks, upgrade management, and disaster recovery compliance with BCP/DR standards
Lead workload rationalization — identifying pipelines, stored procedures, and jobs for consolidation, retirement, or re-architecture
Evaluate and drive adoption of modern data engineering capabilities (Apache Airflow, dbt, AWS Glue, Spark) aligned to Project Catalyst objectives
Own SLA adherence across all data engineering queues — incidents, service requests, small-ticket enhancements, and larger backlog-driven work