Job Title: AWS Site Reliability Engineer (Data Platform)
Role Summary
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 driving 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 IaC and CI/CD.
* Lead resiliency and disaster recovery planning, including regular 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; use error budgets to guide reliability improvements.
* Build and operate robust observability solutions (metrics, logs, traces, alerts) 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 toil and improve platform availability and performance
* Own and drive resolution of incidents and service requests raised by consumer teams, providing operational support for platform usage while identifying recurring issues and automating fixes to improve reliability and user experience.
Required Skills & Experience
* Practical knowledge of SRE principles, including SLO/SLI/SLA design and error budgets.
* Strong experience with AWS (e.g., EC2, S3, IAM, VPC, CloudWatch) in production environments
* Experience with observability tools and monitoring/alerting best practices.
* Hands-on experience with automation and IaC (Terraform, CloudFormation, CDK) and scripting (Python, Bash).
* Exposure to data platforms such as Snowflake and/or 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.