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Bigdata Hadoop Administrator

Job in Lakewood, Ocean County, New Jersey, 08701, USA
Listing for: Quantum Technologies. LLC
Full Time position
Listed on 2026-11-05
Job specializations:
  • IT/Tech
    Data Engineering, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Job Summary

10+ years solid experience with deploying, configuring, monitoring, and troubleshooting Apache Spark clusters and associated big data frameworks (such as Hadoop, Kafka, or cloud-based data platforms) to ensure high availability and performance.

Key Responsibilities
  • Focuses on cluster health, performance tuning, and production data pipelines.
  • Technical

    Experience:

    Deep hands-on experience with Apache Spark architecture (Driver, Workers, Executors, RDDs/Data Frames) and cluster managers (YARN, Kubernetes, or Mesos).
  • OS & Scripting: Strong proficiency in Linux/Unix administration and scripting languages (Bash, Python, or Scala).
  • Ecosystem Knowledge: Familiarity with big data and streaming tools like Hadoop HDFS, Kafka, Hive, or monitoring suites (Splunk, Prometheus, Grafana).
  • Debugging

    Skills:

    Strong analytical capabilities to inspect logs, thread dumps, and metrics under heavy production loads
  • Excellent coordination with stakeholders and communication skills
Must have experience with below responsibilities
  • Cluster Management: Install, configure, and maintain Apache Spark clusters and node infrastructure in production and staging environments.
  • Performance & Monitoring: Monitor cluster health, resource utilization (CPU, memory), and execution logs using tools like Spark UI, Splunk, or Elastic. Identify bottlenecks and optimize job execution times.
  • Troubleshooting: Diagnose and resolve out-of-memory errors, executor failures, shuffle issues, and node crashes in distributed workloads.
  • Pipeline & Integration Support: Support data engineers and developers in managing Spark applications, streaming jobs, and integrations with message brokers like Kafka.
  • Security & Access Control: Implement security principles, role-based access control, authentication, and data encryption across the cluster.
  • Backup & Disaster Recovery: Execute backup, recovery, and failover plans for Spark applications, configurations, and critical data stores.
  • Patching & Upgrades:
    Apply software patches, driver updates, and version upgrades with minimal disruption to ongoing production jobs

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.

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