We are looking for an AWS Site Reliability Engineer (SRE) to support and scale a cloud-native data platform built on AWS, Snowflake, and Databricks.
The role focuses on improving reliability through automation, disaster recovery (DR) testing, resiliency engineering, observability, and proactive SLO/SLI/SLA management.
Key Responsibilities:
Design, build, and maintain automation for infrastructure provisioning, platform operations, and incident response using Infrastructure as Code (IaC) and CI/CD.
Lead resiliency and disaster recovery planning, including DR drills, failure testing, and recovery validation across AWS and data platform components.
Define, implement, and manage SLIs, SLOs, and SLAs for critical data pipelines and platform services, using error budgets to guide reliability improvements.
Build and operate observability solutions covering metrics, logs, traces, and alerting for AWS services, Snowflake, and Databricks workloads.
Partner with data engineering and platform teams to embed reliability-by-design into architecture and delivery practices. Perform root cause analysis (RCA) and drive continuous improvement to reduce operational toil and enhance platform availability and performance.
Own and drive resolution of incidents and service requests raised by consumer teams, providing operational support while identifying recurring issues and automating long-term fixes.
Required Skills and Experience:
Practical knowledge of SRE principles, including SLO/SLI/SLA design and error budgets.
Strong experience with AWS services such as EC2, S3, IAM, VPC, and CloudWatch in production environments.
Experience with observability tools and monitoring/alerting best practices.
Hands-on experience with automation and IaC tools such as Terraform, CloudFormation, or AWS CDK, along with Scripting in Python or Bash.
Exposure to data platforms such as Snowflake and Databricks.
Nice to Have:
Experience running DR tests, chaos engineering, or resiliency testing in cloud environments.
Familiarity with CI/CD pipelines and GitOps practices.
Background supporting large-scale data or analytics platforms.