Hadoop / HPE MapR Engineer

Location: Irving, TX | Phoenix, AZ | Charlotte, NC (Hybrid)
Duration: 12-Month Contract
Level: Software Engineer 3 / Software Engineer 4

Overview

Seeking an experienced Hadoop / HPE MapR Engineer to support and optimize enterprise-scale distributed data platforms in a high-availability production environment. This role focuses on engineering, administration, monitoring, troubleshooting, and performance optimization of HPE MapR-based Hadoop ecosystems supporting large-scale data workloads.

The ideal candidate brings strong experience with distributed systems, Linux administration, Hadoop technologies, Apache Spark, and enterprise production support.

Key Responsibilities

• Design, build, maintain, and optimize large-scale Hadoop and HPE MapR data platforms
• Support enterprise distributed systems with focus on scalability, performance, reliability, and availability
• Administer and troubleshoot HPE MapR clusters in production environments
• Monitor cluster health, storage utilization, processing performance, and system stability
• Resolve complex infrastructure and application issues across distributed environments
• Support batch and stream data processing workloads using Apache Spark and related technologies
• Perform Linux/Unix administration tasks, scripting, automation, and operational support
• Collaborate with engineering, infrastructure, and architecture teams on platform enhancements and operational improvements
• Support high-availability configurations and enterprise resiliency initiatives
• Utilize monitoring and observability tools to identify, analyze, and resolve system issues
• Participate in operational support, incident resolution, root cause analysis, and performance tuning initiatives

Required Qualifications

Software Engineer 3

• 3 5 years of experience in software engineering, big data engineering, infrastructure engineering, or distributed systems support
• Hands-on experience with Hadoop ecosystems, specifically HPE MapR
• Strong understanding of distributed systems, cluster computing, and enterprise data platforms
• Experience administering Linux/Unix systems in enterprise environments
• Experience with one or more scripting/programming languages:
  
  
  
  • Python
  • Java
  • Scala
  • Bash/Shell
  
  
• Experience with Apache Spark and distributed data processing frameworks
• Experience supporting enterprise production environments with high availability requirements
• Strong troubleshooting and performance tuning experience
• Familiarity with monitoring tools such as Grafana, Prometheus, Splunk, or similar platforms

Software Engineer 4

• 5+ years of experience in software engineering, big data engineering, infrastructure engineering, or distributed systems support
• Advanced hands-on expertise with Hadoop ecosystems and HPE MapR platforms
• Deep understanding of distributed storage, cluster operations, scalability, and resiliency
• Strong enterprise production support and operational engineering experience
• Advanced troubleshooting and performance optimization capabilities within large-scale distributed environments
• Experience supporting mission-critical enterprise data platforms

Preferred Skills

• Experience with enterprise-scale Hadoop migrations or modernization initiatives
• Knowledge of streaming technologies and data pipeline architectures
• Experience with automation, infrastructure scripting, or platform reliability engineering
• Familiarity with enterprise compliance and operational standards
• Experience working in Agile delivery environments

Ideal Candidate

• Strong hands-on engineer with enterprise Hadoop and HPE MapR expertise
• Comfortable operating in complex, large-scale production environments
• Experienced troubleshooting distributed systems and performance bottlenecks
• Able to balance operational support with platform engineering improvements
• Effective communicator who can collaborate across engineering and infrastructure teams