Lead Hadoop / HPE MapR Engineer

Please find details for this position below: Client: Banking/Financial Industry Title: Lead Hadoop Developer / Lead HPE MapR Engineer / Lead BigData/Hadoop Developer Location: Charlotte, NC - Hybrid Role Duration: 12+ Months (s) Contract to hire, or possibility to extension Job Description: • In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Software Engineering. • Review and analyze complex multi-faceted, larger scale or longer-term Software Engineering challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors. • Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. • Strategically collaborate and consult with client personnel. Required Qualifications: • 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education. • 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). • 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. • 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. EEO: Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.