Bigdata Hadoop Administrator

Machine Learning Technologies, LLC; Berkeley Heights (NJ); On-site; USD 150,000 - 210,000; Full time

Job summary

Machine Learning Technologies, LLC seeks an experienced Spark infrastructure engineer to deploy, configure, monitor, and troubleshoot Apache Spark clusters and related big data platforms in production environments.

You will own cluster health, performance tuning, and data pipelines, while collaborating with data engineers and developers on Spark applications, streaming jobs with Kafka, and integration with monitoring suites like Splunk, Prometheus, and Grafana.

Qualifications

• Experience deploying and maintaining Spark clusters in production.
• Strong Linux/Unix scripting and automation skills.
• Familiarity with monitoring and log-analysis tools (Splunk, Prometheus, Grafana).

Responsibilities

• Maintain cluster health, optimize performance, and ensure data pipeline reliability.
• Work with Spark architecture components: Driver, Executors, RDDs/DataFrames.
• Monitor resource usage and troubleshoot OOM, failures, and bottlenecks.
• Support data engineers and developers with Spark apps and Kafka integrations.
• Implement security, access control, and disaster recovery for clusters.
• Collaborate with stakeholders and communicate findings clearly.

Skills

Spark architecture

Cluster health monitoring

Linux scripting

Big data tooling

Debugging logs

Stakeholder communication

Tools

Spark UI

Splunk

Prometheus

Grafana

Kafka

Hadoop

Hive

Kubernetes

YARN

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.