Product Support Engineer (Hadoop)

TL;DR

Product Support Engineer (Hadoop/Spark): Providing tier-2/3 technical support and optimization for Hadoop-based data processing systems with an accent on cluster reliability and performance tuning. Focus on deep-dive debugging of HDFS, YARN, and Hive/Impala to ensure high-throughput performance for enterprise big data workloads.

Location: Remote (Must be based in the United States and able to bridge EST and PST hours)

Salary: $80,000 - $100,000 a year

Company

Market leader in Enterprise Data Observability providing a SaaS platform to help build and operate great data products.

What you will do

• Provide tier-2/3 support for data or performance issues in Hadoop clusters across the entire technical stack.
• Conduct deep-dive debugging and optimization of Hadoop clusters, including NiFi, Impala, and Spark jobs.
• Lead product support during ODP Hadoop migrations and upgrades to ensure post-migration stability.
• Design and optimize distributed Hadoop-based applications for low-latency and high-throughput performance.
• Take ownership of complex customer environments and mentor junior team members.

Requirements

• 5+ years of hands-on experience working with Hadoop environments.
• Technical proficiency in core Hadoop services (HDFS, YARN, Hive/Impala) and knowledge of Kafka, NiFi, Ambari, and Cloudera Manager internals.
• Advanced skills in configuring, tuning, and troubleshooting Red Hat and Debian-based Linux distributions.
• Ability to provide weekend coverage and pivot working hours to bridge the gap between EST and PST.

Nice to have

• Proficiency in Python, Bash, or Scala for system automation and performance monitoring.

Culture & Benefits

• Culture that values an ‘out-of-the-box’ mindset and continuous learning.
• Opportunity to work with industry-leading minds on mission-critical projects.
• Equitable workplace committed to providing equal employment opportunities for all.
• Collaborative environment with highly capable and ambitious peer groups.