16 hours ago
Hyderābād, IndiaSenior
Responsibilities
- Develop synthetic workload queries and datasets for testing DPA-S.
- Build analysis and diagnostic tools for DPA-S, Apache Spark, and deployment-environment logs.
- Address or escalate customer support issues through the product support rotation.
- Conduct end-to-end product validation and execute test plans.
- Analyze validation artifacts and customer issues to identify tuning opportunities, usage recommendations, and product bugs.
- Use automation and AI techniques across product validation and support processes.
- Create bug reports, RCA documents, configuration guides, and best-practice documents.
Requirements
- At least 5 years of experience developing, validating, and supporting enterprise data processing software products.
- At least 2 years of experience providing direct support to external customers.
- At least 2 years of experience supporting Apache Spark pipelines for data engineering and analytics.
- Proficiency running Spark jobs, provisioning Spark resources, configuring and tuning Spark parameters, using Spark History Server and Spark UI, and analyzing Spark event logs and other Spark logs.
- Solid knowledge of SQL and Python.
- Proficiency in testing data products and test automation.
- Understanding of deployment and operations for data processing products and pipelines in SaaS, VM-based, container-based, and serverless environments.
- Experience with GCP, AWS, and their Apache Spark offerings is preferred.
- Good customer engagement and communication skills.
Categories
Data EngineeringTesting
About NetApp
NetApp builds data storage and data management software and hardware for enterprises, including ONTAP-powered all-flash arrays and hybrid cloud services that integrate with AWS, Azure, and Google Cloud. It sells systems and subscriptions that support backup, disaster recovery, databases, and container/Kubernetes workloads. Founded in 1992 and headquartered in San Jose, California, NetApp is a public company listed on NASDAQ.