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Strong Tier-1 brand but senior, specialized SRE role reduces general applicant density.
High because role requires deep SRE, cloud, Databricks, and big-data platform expertise, limiting cross-industry transferability.
High due to explicit 10+ years requirement and mandatory SRE, Terraform, Python, and Databricks skills.
Lead and manage an SRE team to design, implement, and support a managed AWS Databricks platform for business-critical services.
Develop and execute multi-AZ, multi-region, and multi-cloud resiliency strategies and drive continuous platform observability, alerting, and capacity planning improvements.
Leverage enterprise-authorized AI capabilities to enhance reliability workflows, ensure secure and compliant AI usage, and apply SRE best practices to improve system reliability, scalability, and performance.
10+ years of applied software engineering experience with formal training or certification in software engineering concepts.
Strong understanding of SRE principles including SLIs, SLOs, error budgets, incident management, and proficiency in Python development with automated unit testing.
Experience with monitoring tools, automation frameworks, CI/CD pipelines, Terraform development, and knowledge of Big Data compute frameworks like Spark, Glue, and MapReduce.
Demonstrated use of enterprise-authorized AI tools for reliability engineering with awareness of data sensitivity; experience setting team practices for safe AI usage in operations.
Experienced leader comfortable managing SRE teams and driving platform architecture in cloud environments with business-critical impact.
Deep knowledge of AWS Databricks platform administration, big data processing frameworks, and infrastructure automation using Terraform.
Strategic operator skilled in integrating AI-driven workflows in reliability engineering while maintaining security, compliance, and operational resilience.