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# Sr. Site Reliability Engineer, S3 storage

- **Company:** Tesla, Inc.
- **Location:** Fremont, CA, United States
- **Experience:** Expert
- **Salary:** $168,000.0 - $252,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Systems Engineering, Confluence, Bash Shell, Cloud Storage, Data Compression, Computer Programming, Computer Engineering, System Configuration, Information Engineering, Data Security, DevOps, Distributed Systems, Python (Programming Language), Open Source Technology, Reliability Engineering, Ansible, Prometheus, Software Engineering, Management of Software Versions, S3 Bucket, Data Ingestion, Grafana, Apache Spark, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Functional Programming, Cloudwatch, Terraform, Splunk, Docker, Golang
- **Published:** October 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fcdf69eb1ba1e50c

## About the Role

You'll de responsible for optimizing data ingestion, retrieval, and archival processes to handle high-throughput workloads, reducing costs through intelligent tiering (e.g., S3 Intelligent-Tiering) and data compression. You will ensure storage systems comply with data protection standards (e.g., GDPR, SOC 2), implementing features like bucket policies, versioning, and encryption at rest/transit. You will work with data engineering, AI, and energy teams to integrate S3 with other systems (e.g., Kubernetes, Spark). You will contribute to open-source tools or internal projects for advanced storage solutions and maintain runbooks, contribute to knowledge bases (e.g., in Confluence), and mentor junior engineers on best practices for object storage reliability., * Degree in Computer Science, Engineering, Software Engineering, Computer Engineering, or a related field, and 5 years of post baccalaureate, progressive work experience in SRE, DevOps, or systems engineering roles, or equivalent experience

 * Must have 3 years of experience in one or a combination of the following object storage platforms: AWS S3, GCS, or Azure Blob
 * 3 years of experience managing large-scale (PB-level) storage systems
 * 2 years of experience in the following AWS services: S3, EC2, Lambda, and CloudWatch
 * 5 years of experience in the following infrastructure tools: Terraform, Kubernetes, and Docker;
 * Experience in scripting and programming for automation and tooling using Python, Go and Bash
 * 5 years of experience in one or a combination of the following distributed systems, networking, and storage concepts: eventual consistency, or CRR/SRR replication
 * 5 years of experience with Prometheus, Grafana, and Splunk

## Description

* Design and implement monitoring, alerting, and automation for S3 storage clusters to achieve 99.99%+ uptime
 * Use tools like Prometheus, Grafana, or Catchpoint to track performance metrics, capacity utilization, and anomaly detection
 * Forecast storage needs based on data growth trends (e.g., fleet expansion exceeding 80 PB) and proactively scale S3 buckets, lifecycle policies, and multi-region replication to support up to 150 PB+ capacities
 * Lead on-call rotations, troubleshoot storage-related incidents (e.g., data access latency, replication failures), and perform root cause analysis using methodologies like blameless post-mortems
 * Develop and maintain automation scripts (e.g., using Terraform, Ansible, or Python) for provisioning, configuring, and managing S3 resources, including security policies, encryption, and access controls
 * Optimize data ingestion, retrieval, and archival processes to handle high-throughput workloads, reducing costs through intelligent tiering (e.g., S3 Intelligent-Tiering) and data compression
 * Ensure storage systems comply with data protection standards (e.g., GDPR, SOC 2), implementing features like bucket policies, versioning, and encryption at rest/transit
 * Work with data engineering, AI, and energy teams to integrate S3 with other systems (e.g., Kubernetes, Spark)
 * Contribute to open-source tools or internal projects for advanced storage solutions
 * Maintain runbooks, contribute to knowledge bases (e.g., in Confluence), and mentor junior engineers on best practices for object storage reliability