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# Site Reliability Engineer

- **Company:** Software Technology, Inc.
- **Location:** Princeton, United States (Remote available)
- **Experience:** Expert
- **Contract:** Temporary to permanent
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Apache HTTP Server, Big Data, Cloud Computing, Cloud Engineering, System Configuration, Continuous Integration, Data Infrastructure, Data Security, Software Debugging, Linux, Distributed Systems, Apache Hadoop, Monitoring of Systems, Identity and Access Management, Java Virtual Machine (JVM), Python (Programming Language), Kerberos (Protocol), Linux System Administration, Log Analysis, Performance Tuning, Reliability Engineering, Site Reliability Engineering Practices, Cloudera, Systems Integration, Scripting, Apache Spark, Infrastructure as Code (IaC), AWS Glue, Data Management, Virtual Agents, Cloudwatch, Terraform, Heap (Data Structure), AWS EKS, Amazon Elastic Mapreduce (EMR)
- **Published:** July 23, 2026
- **Apply:** https://www.dice.com/job-detail/577e61cb-3a8d-488a-baef-8d0d19c32370

## About the Role

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, 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., 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, 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, 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.

Preferred Candidate Profile

The ideal candidate combines deep expertise in AWS cloud platforms, Hadoop ecosystems, SRE practices, observability, automation, and AI-driven operations, with a passion for supporting resilient data platforms at scale and eliminating operational toil through engineering excellence.

## Description

* 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.


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