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
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