Data Platform Engineering Manager

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The Data Platform Engineering Manager role is responsible for designing, building, and operating the enterprise technology reference data platform that serves as the foundation for technology governance, reporting, analytics, metrics, and decision-making. Reporting to the Head of Technology Data   Management , this role leads the onboarding, integration, transformation, and delivery of technology data from infrastructure, cyber, cloud, AI, and enterprise systems into a Databricks-based data fabric.   The role is accountable for establishing scalable data ingestion patterns, integration frameworks, platform engineering standards, and operational controls that ensure technology data is accurate, accessible, reliable, secure, and consumable. This position plays a critical leadership role in enabling enterprise-wide data products, dashboards, KPIs, risk reporting, and operational insights through modern data engineering and platform capabilities.   KEY ACOUNTABILITIES Data Platform Strategy & Enablement   Lead the design, implementation, and evolution of the Databricks-based technology reference data platform.   Develop platform standards, engineering patterns, and operating procedures that support enterprise scalability and sustainability.   Establish a modern data ecosystem capable of supporting governance, reporting, analytics, and AI-driven use cases.   Drive platform modernization initiatives that improve performance, automation, resilience, and user experience.   Data Ingestion & System Onboarding   Lead onboarding of technology systems of record into the enterprise data platform.   Design and implement scalable integration patterns including APIs, event-driven   architectures , data streaming, and zero-copy data sharing.   Establish standards for source system connectivity, transformation, validation, and data movement.   Partner with source system owners to ensure data is delivered accurately, securely, and efficiently.   Data Engineering & Transformation   Design, build, and manage data pipelines that transform disparate source data into standardized enterprise data assets.   Develop reusable ingestion and transformation frameworks that accelerate onboarding of new data sources.   Implement automated controls to ensure data quality, integrity, completeness, and consistency.   Optimize data processing and storage solutions to support large-scale technology data domains.   Data Operations & Reliability   Establish monitoring and observability capabilities to ensure platform health and data reliability.   Define operational support processes, service-level agreements, and issue management procedures.   Lead remediation efforts for data delivery issues, performance bottlenecks, and platform incidents.   Ensure platform availability, resiliency, and business continuity requirements are met.   Data Security, Controls & Compliance   Ensure compliance with enterprise security, data protection, and regulatory requirements.   Implement access controls, encryption standards, audit logging, and monitoring capabilities.   Partner with Risk, Security, and