Acceldata20d ago

Hadoop Product Support Engineer

BengaluruRemoteFull-Timemid

OtherTechnical Support EngineerCustomer

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ABOUT US Acceldata is the market leader in Enterprise Data Observability. Founded in 2018,

Technical Tools

OtherTechnical Support EngineerCustomer

Acceldata is the market leader in Enterprise Data Observability. Founded in 2018, Silicon Valley-based Acceldata has developed the world's first Enterprise Data Observability Platform to help build and operate great data products.

Enterprise Data Observability is at the intersection of today’s hottest and most crucial technologies such as AI, LLMs, Analytics, and DataOps. Acceldata provides mission-critical capabilities that deliver highly trusted and reliable data to power enterprise data products.

Delivered as a SaaS product, Acceldata's solutions have been embraced by global customers, such as HPE, HSBC, Visa, Freddie Mac, Manulife, Workday, Oracle, PubMatic, PhonePe (Walmart), Hersheys, Dun & Bradstreet, and many more. Acceldata is a Series-C funded company and its investors include Insight Partners, March Capital, Lightspeed, Sorenson Ventures, Industry Ventures, and Emergent Ventures.

As a product support engineer, you are expected to take ownership of complex customer environments, mentor junior team members, and drive the reliability of Hadoop and Spark-based data processing systems. You will collaborate closely with customer engineering teams to deliver high-throughput Hadoop and Spark applications, solve complex data challenges during migration and upgrades, ensure reliability, and optimise post-migration system performance.

Strong desire to tackle hard technical problems in Hadoop and proven ability to do so with little or no direct daily supervision.

Troubleshooting: Provide tier-2/3 support for data or performance issues in Hadoop clusters across the entire technical stack.

Debugging: Conduct deep-dive debugging and optimisation of Hadoop clusters, including NiFi, Impala, and Spark jobs.

Migration: Lead product support during ODP Hadoop migrations, upgrades, ensuring post-migration stability, addressing upgrades and evolving technical hurdles.

Optimisation: Design and optimise distributed Hadoop-based applications to ensure low-latency, high-throughput performance for big data workloads.

Experience: 5+ years of hands-on experience working with hadoop environments.

Technical proficiency in core hadoop services (HDFS, YARN, and Hive/Impala) and good working knowledge of Kafka, NiFi, Ambari, and Cloudera Manager internals.

Extensive experience in troubleshooting and debugging hadoop components.

Linux: Advanced skills in configuring, tuning, and troubleshooting Red Hat and Debian-based distributions.

Good to have proficiency in Python, Bash, or Scala for system automation and performance monitoring.