Bigdata Hadoop Administrator
Robotics Technologies LLC
Kettering, OH, United States
4 days ago
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Role details
Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source
Tech stack
User Authentication
Bash Shell
Big Data
System Configuration
Data Stores
Software Debugging
Apache Hadoop
Hadoop Distributed File System
Apache Hive
Python (Programming Language)
Message Broker
Node.Js
+17 more
Operational Databases
Performance Tuning
Role-Based Access Control
Prometheus
Mesos
Data Streaming
Systems Integration
Backup and Restore
Scripting
Cloud Platform System
Apache Yarn
System Availability
Grafana
Apache Spark
Kubernetes
Apache Kafka
Splunk
Job description
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., * Focuses on cluster health, performance tuning, and production data pipelines., * 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
Requirements
- 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
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