Strategic Platform Leadership
• Co-own and evolve the overall data platform architecture across all domains
• Guide the technical vision for the entire Data Engineering organization
• Drive platform initiatives that directly support the company’s data strategy
• Lead the modernization of legacy systems while ensuring business continuity
• Identify and solve problems that span the entire Data Engineering org before they impact delivery
• Set the bar for excellence and serve as an inspiration across all engineering teams
Architecture & Technical Excellence
• Design and drive implementation of highly scalable platform architectures for multi-TB+ daily workloads
• Author and sign off on all RFCs and technical specifications that touch your domain(s)
• Define best practices and patterns that become standard across the organization
• Build self-service infrastructure that empowers hundreds of data consumers while maintaining reliability
• Design event-driven, real-time data architectures using Kafka and stream processing at scale
• Contribute to any codebase across the organization, setting quality standards through exemplary code
Platform Engineering Excellence
• Architect comprehensive Infrastructure as Code strategies and GitOps frameworks
• Design enterprise-grade security frameworks including encryption, zero-trust access controls, and compliance
• Establish SLAs/SLOs for critical platform services and drive observability strategy
• Lead complex incident response, conduct thorough post-mortems, and implement systemic improvements
• Drive platform reliability and performance optimization initiatives
• Mentor IC9 and IC10 engineers, accelerating their technical growth and impact
• Collaborate across the entire Engineering organization as a thought partner
• Interact with executives and external stakeholders as a domain expert
• Democratize data access by empowering more teams to contribute to the data stack safely
• Identify hiring gaps and help define interview panels for critical technical roles
• Actively participate in and contribute to Data Engineering communities (conferences, Stack Overflow, vendor forums)