Bigdata Hadoop Administrator

Ethereum Technologies LLC; Berkeley Heights (NJ); On-site; USD 180,000 - 280,000; Full time

Job summary

Ethereum Technologies is seeking a senior Big Data Engineer with 10+ years of hands-on experience deploying, configuring, monitoring, and troubleshooting Apache Spark clusters to ensure high availability and peak performance across production and staging environments.

You will own cluster health and performance tuning, manage security and access controls, oversee upgrades and DR plans, and collaborate with data engineers on Spark applications, Kafka integrations, and cloud data platforms to

Qualifications

• 10+ years solid experience with deploying, configuring, monitoring, and troubleshooting Apache Spark clusters and related big data platforms.

Responsibilities

• Cluster Management: Install, configure, and maintain Spark clusters and node infrastructure in production and staging environments.
• Performance & Monitoring: Monitor cluster health, resource utilization, and execution logs using Spark UI, Splunk, or Elastic.
• 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 Kafka integrations.
• Security & Access Control: Implement RBAC, authentication, and data encryption across the cluster.
• Backup & Disaster Recovery: Execute backup, recovery, and failover plans for Spark applications and configurations.
• Patching & Upgrades: Apply software patches and driver updates with minimal disruption to production jobs.

Skills

Spark architecture

Cluster health monitoring

Linux administration

Scripting languages

Analytical debugging

Communication skills

Tools

Spark UI

Splunk

Prometheus

Grafana

YARN

Kubernetes

Mesos

Kafka

Hadoop

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.