Bigdata Hadoop Administrator

Quantum Technologies. LLC; New Jersey; On-site; USD 120,000 - 180,000; Full time

Job summary

Quantum Technologies. LLC seeks a highly skilled data engineering specialist to deploy, configure, monitor, and troubleshoot Apache Spark clusters and associated big data frameworks.

The role emphasizes high availability, performance, and secure access across production environments. You will focus on cluster health, performance tuning, and supporting data engineers with streaming pipelines and integrations with Kafka, Hadoop, and cloud platforms.

Qualifications

• Expertise deploying and managing Spark clusters in production.
• Experience with Hadoop, Kafka, and cloud data platforms.
• Strong Linux/Unix scripting (Bash, Python, Scala).

Responsibilities

• Maintain Spark clusters for high availability and performance.
• Tune performance, monitor pipelines, and investigate bottlenecks.
• Troubleshoot OOMs, executor failures, and shuffle issues.
• Collaborate with data engineering and DevOps teams on deployments.
• Ensure security and access control across the cluster.

Skills

Spark architecture

Linux scripting

Python

Scala

Kafka

Hadoop

Monitoring tools

Troubleshooting

Stakeholder communication

Tools

Spark UI

Kubernetes

YARN

HDFS

Prometheus

Grafana

Splunk

Elastic

Job description

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.