• Lead a team of SREs to design, implement, and maintain a managed AWS Databricks platform, providing engineering and operational support to Application/Engineering teams
• Perform platform design, set-up and configuration, workspace administration, and resource monitoring
• Create multi-AZ, multi-region, and multi-cloud resiliency strategies for business-critical products and services
• Lead evaluation sessions with external vendors, startups, and internal teams to assess architectural designs and technical credentials
• Drive continuous improvement in system observability, alerting, and capacity planning
• Collaborate with engineering and data teams to optimize infrastructure and deployment processes, focusing on automation and operational excellence
• Execute creative software solutions, design, development, and technical troubleshooting
• Uses enterprise-authorized AI capabilities within the work environment to accelerate reliability design and operational decisioning (e.g., incident/post-incident analysis and requirements traceability), validating outputs and handling operational data according to sensitivity and security requirements.
• Leads reuse-first adoption of AI-assisted reliability workflows across SDLC/toolchain practices (e.g., testing/validation automation and production readiness), ensuring traceability/auditability, resiliency, and security controls.
• Develop secure, high-quality production code, and review/debug code written by others to ensure reliability and correctness.
• Apply SRE best practices to improve reliability, scalability, and performance; eliminate or automate recurring issues; and maintain incident response procedures including root cause analysis and postmortems.

Required qualifications, capabilities and skills

• Formal training or certification on software engineering concepts and 10+ years applied experience
• Strong understanding of SRE principles, including SLIs, SLOs, error budgets, and incident management
• Experience with monitoring tools, automation frameworks, and CI/CD pipelines
• Proficient in Python application program development with use of automated unit testing
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to improve reliability engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to set team practices for safe AI usage in operations (e.g., review/approval expectations and escalation paths) while maintaining resiliency, security, and auditability outcomes.
• Experience with Terraform development and understanding of Terraform enterprise
• Experience in delivering system design, application development, testing, and operational stability
• Knowledge of Big Data distributed compute frameworks like Spark, Glue, MapReduce
• Excellent troubleshooting, analytical, and communication skills

Preferred qualifications, capabilities and skills

• Experience in Data pipelines using Spark
• Exposure to AWS & Databricks Platform administration
• Knowledge of containerization (Docker, Kubernetes) and orchestration
• Familiarity with distributed systems and large-scale data processing