Hadoop Product Support Engineer

About Us

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

Enterprise Data Observability is at the intersection of todays 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, Acceldatas 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.

Key Responsibilities

• 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.

Technical Qualification

• 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.

At Acceldata, we are committed to providing equal employment opportunities regardless of job history, disability, gender identity, religion, race, color, caste, marital/parental status, veteran status or any other special status. We stand against the discrimination of employees and individuals and are proud to be an equitable workplace that welcomes individuals from all walks of life if they fit the designated roles and responsibilities.

Life @ Acceldata

is all about working with some of the best minds in the industry and experiencing a culture that values an out-of-the-box mindset. If you want to push boundaries, learn continuously and grow to be the best version of yourself, Acceldata is the place to be!

We also believe in providing our employees with the right tools and resources to help them excel at their job.

What should you know about joining Acceldata

At Acceldata, each job and role serves a purpose towards our business goals. Youll have opportunities to make an immediate impact on mission-critical projects as you work with highly capable and ambitious peer groups.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.