Description

Skills : (AWS, Hadoop, on-premises, AI)

Skills - Site Reliability Engineering, Big Data, AWS, AWS EMR, AWS EKS, AWS MSK, AWS Athena, AWS Glue, Spark, Iceberg, Python, Terraform, Cloudera Hadoop, Agentic Ai, Monitoring Tools Role Overview We are seeking a highly skilled L2+/Senior Data Infrastructure Site Reliability Engineer (SRE) to operate, optimize, and automate large-scale data infrastructure environments across AWS and on-premises Hadoop platforms.

This role requires a strong reliability engineering mindset focused on platform stability, performance, observability, automation, and incident response.

As a key member of the Data Infrastructure SRE team, you will ensure the availability, scalability, security, and operational excellence of mission-critical data platforms while driving continuous improvements through Infrastructure as Code (IaC), AI-enabled automation, and modern SRE practices.

Key Responsibilities

• Maintain and support highly available, scalable, and secure data infrastructure platforms across AWS and on-premises environments.
• Drive operational excellence through automation of repetitive tasks, incident reduction, and proactive reliability improvements.
• Monitor platform health, troubleshoot complex issues, and lead root cause analysis efforts to minimize downtime and improve system resiliency.
• Collaborate closely with engineering, platform, and data teams to support deployments, integrations, upgrades, and performance optimization initiatives.
• Participate in on-call rotations and partner with teams across the US and India to provide 24x7 operational support. US support is aligned to Pacific Time zone.
• Continuously improve observability, alerting, and incident response processes to enhance platform reliability and reduce operational noise.

Required Skills & Experience

• Site Reliability Engineering (SRE)
• Strong SRE mindset with a proven focus on reliability, availability, performance optimization, incident management, and operational excellence.
• Experience delivering services within defined SLAs and ensuring timely resolution of production issues.
• Expertise in troubleshooting complex distributed systems and identifying root causes quickly and effectively.
• AWS & Cloud Infrastructure
• Deep hands-on experience with AWS services, including: EMR, EKS, MSK, Athena, Glue, IAM, Amazon S3, VPC, AWS networking and security services
• Strong understanding of cloud-native architectures, scalability, and infrastructure resilience.
• Big Data Platforms
• Extensive operational experience managing Hadoop clusters, with a strong focus on administration, platform maintenance, and automation of day-to-day operational activities.
• Experience supporting both AWS-based data platforms and on-premises Cloudera CDH/CDP environments.
• Solid understanding of Kerberos authentication and security implementation within Hadoop ecosystems.
• Hands-on experience with: Apache Spark, Apache Iceberg, Big Data platform architecture, Performance tuning and optimization
• Linux & System Administration
• Strong Linux administration and operational support experience.
• Expertise in user and access management, system configuration, customization, and platform administration.
• Observability & Incident Management
• Hands-on experience with monitoring and observability platforms such as: AWS CloudWatch, Datadog, PagerDuty, Similar enterprise monitoring solutions
• Proven success improving alert quality, reducing false positives, and minimizing alert fatigue.
• Excellent debugging and troubleshooting skills across infrastructure, applications, Spark workloads, and Iceberg environments.
• Java Platform Operations
• Strong understanding of Java application administration, including: JVM tuning, Thread dump analysis, Heap dump analysis, JVM parameters, Application log analysis and troubleshooting
• Automation & Infrastructure as Code
• Expert-level Python scripting for operational automation, monitoring, and reliability engineering use cases.
• Strong experience with: Terraform, Infrastructure as Code (IaC), CI/CD pipeline implementation and automation, Platform engineering best practices
• AI-Driven Operations
• Current hands-on experience applying AI technologies to Data Infrastructure and SRE operations.
• Demonstrated ability to design and implement: Agentic AI solutions, AI-assisted operational workflows, Intelligent automation for routine SRE activities
• Strong creativity and problem-solving skills in leveraging AI to improve operational efficiency, reliability, and productivity

Key Skills

Education

Any Graduate