Bigdata Hadoop Administrator

Valiant Technologies LLC; Berkeley Heights (NJ); On-site; USD 150,000 - 230,000; Full time

Job summary

Valiant Technologies LLC is seeking a senior big data engineer to deploy, configure, monitor, and troubleshoot Apache Spark clusters and related big data platforms. The role focuses on cluster health, performance tuning, and production data pipelines to ensure high availability and reliability.

You will work with Hadoop, Kafka, and cloud-based platforms, applying expertise in Spark architecture, cluster managers, and monitoring tools.

Qualifications

• 10+ years experience deploying, configuring, monitoring and troubleshooting Spark clusters.
• Deep hands-on Spark architecture experience and familiarity with cluster managers (YARN/Kubernetes/Mesos).
• Strong Linux/Unix administration and scripting skills (Bash, Python, Scala).
• Experience with Hadoop, Kafka, Hive and monitoring suites (Splunk, Prometheus, Grafana).

Responsibilities

• Cluster management: install, configure, and maintain Spark clusters and node infra in prod/staging.
• Performance & monitoring: track cluster health, CPU/memory, and logs; optimize jobs.
• Troubleshooting: diagnose OOMs, executor failures, shuffle issues, node crashes.
• Pipeline & integration support: assist data engineers with Spark apps and streaming jobs.
• Security & access control: implement RBAC, authentication, and data encryption.
• Backup & disaster recovery: plan and execute backup, recovery, and failover for Spark apps.
• Patching & upgrades: apply patches and driver updates with minimal disruption.

Skills

Spark architecture expertise

Cluster health & performance tuning

Linux/Unix administration

Scripting: Bash, Python, Scala

Stakeholder coordination & strong comm

Tools

Apache Spark

YARN

Kubernetes

Mesos

Hadoop HDFS

Kafka

Hive

Splunk

Prometheus

Grafana

Spark UI

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.