STRATEGIC STAFFING SOLUTIONS HAS AN OPENING!
This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position. Visa Sponsorship is Available! The details are below.
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Job Title: Hadoop / HPE MapR Engineer
Contract Length: 12+ Month contract
Hybrid Work (Some on site work)
Location: Charlotte, NC
Ref# 245985
We are seeking a skilled Hadoop / HPE MapR Engineer to design, build, operate, and optimize large-scale distributed data platforms. This role focuses on supporting and enhancing HPE MapR based Hadoop ecosystems, ensuring high availability, performance, security, and reliability for enterprise data workloads.
The ideal candidate has hands-on experience with MapR services, distributed systems, Linux, and big data processing frameworks, and is comfortable operating in a complex, production-grade environment.
Key Responsibilities
- Design, build, operate, and optimize Hadoop-based data platforms using HPE MapR
- Support and enhance MapR-based Hadoop ecosystems in enterprise environments
- Ensure high availability, performance, security, and reliability of data platforms
- Troubleshoot performance and stability issues in large-scale distributed systems
- Support production, enterprise-scale clusters with high availability requirements
Required Qualifications
- Strong hands-on experience with Hadoop distributions, specifically HPE MapR
- Deep understanding of distributed systems, data storage, and cluster computing concepts
- Proficiency in Linux/Unix system administration
- Experience with at least one programming or scripting language: Python, Java, Scala, or Bash
- Working knowledge of Spark and batch/stream processing paradigms
- Experience troubleshooting performance and stability issues in large-scale environments
- 5+ years of experience in big data, data platform, or infrastructure engineering roles
- Experience supporting production, enterprise-scale clusters with high availability requirements
- Familiarity with monitoring tools (e.g., Grafana, Prometheus, Splunk, or similar)
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