Job Description

Locations

• Bengaluru, Karnataka, India

Skills Required

• AWS servicesintermediate
• scripting/programmingintermediate
• monitoringintermediate

Required Qualifications

• Experience: 5+ years in SRE, DevOps, or systems engineering roles, with at least 3 years focused on AWS S3 or similar object storage (e.g., GCS, Azure Blob). Proven track record managing large-scale (PB-level) storage systems. (experience, 5 years)
• Technical Skills: (experience)
• Expertise in AWS services (S3, EC2, Lambda, CloudWatch) and infrastructure tools (Terraform, Kubernetes, Docker). (experience)
• Proficiency in scripting/programming (Python, Go, Bash) for automation and tooling. (experience)
• Strong understanding of distributed systems, networking, and storage concepts (e.g., eventual consistency, CRR/SRR replication). (experience)
• Experience with monitoring and logging tools (Prometheus, Grafana, Splunk). (experience)
• Soft Skills: Excellent problem-solving abilities, strong communication skills, and a collaborative mindset. Ability to thrive in a fast-paced, high-stakes environment. (experience)
• Education: Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience). (experience)

Responsibilities

• System Reliability and Monitoring: 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.
• Capacity Planning and Scaling: 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.
• Incident Management: 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.
• Automation and Infrastructure as Code: 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.
• Performance Optimization: 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.
• Security and Compliance: Ensure storage systems comply with data protection standards (e.g., GDPR, SOC 2), implementing features like bucket policies, versioning, and encryption at rest/transit.
• Collaboration and Innovation: 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.
• Documentation and Knowledge Sharing: Maintain runbooks, contribute to knowledge bases (e.g., in Confluence), and mentor junior engineers on best practices for object storage reliability.

Tags & Categories