Software Engineer 4
Job Summary
As a Senior Software Engineer for DataPelago data processing customer success, you will develop workload assets and automation tools for product validation and product support which will help ensure customers deploy and operate DataPelago data processing products successfully in production. You will apply AI effectively in combination with the knowledge from both product validation and product support to proactively avoid bugs and issues and to drastically reduce time to diagnose, mitigate, and resolve bugs and issues.
Job Requirements
What You'll Do:
- Design, Develop synthetic workload queries and datasets for testing DPA-S, which reflect the essential environment and workload characteristics represented in the field.
- Develop analysis and diagnostic tools that analyze various logs from DPA-S, Apache Spark, and their deployment environment to aid in pinpointing the root cause of functional and performance anomalies and potential mitigations and resolutions.
- Field and address or escalate customer support issues as part of the product support rotation.
- Conduct end-to-end product validation, collaborating with others to define, review, and execute test plans.
- Analyze artifacts from product validation testing and issues raised by customers to identify potential configuration tuning opportunities, product usage recommendations, and product bugs.
- Leverage automation and AI techniques effectively in the entire process of product validation and product support.
- Create bug reports, RCA documents, configuration guides, and best practice documents.
What You'll Bring:
- 8+ years of experience related to development, validation and support of enterprise data processing software products.
- 4+ years of experience providing direct support to external customers.
- 4+ years of experience supporting Apache Spark pipelines for data engineering, analytics. Proficient in running Spark jobs from various clients, Spark resource provisioning, Spark parameter configuration and tuning, using Spark History Server and Spark UI, analyzing Spark event logs and other Spark logs.
- Solid knowledge of SQL and Python.
- Proficient in testing data products and test automation.
- Good understanding of the deployment, and operations of data processing products and pipelines in the cloud – in SaaS, VM-based, container-based, and serverless scenarios. Experience with GCP, AWS, and their Apache Spark related offerings preferred.
- Good customer engagement and communication skills.
Education
- A minimum of 8 years of experience is required. 8 to 12 years of experience is preferred.
- 8+ years of experience related to development, validation and support of enterprise data processing software products.
All internal movements within the Product Group via requisition will be lateral, offering valuable growth opportunities to extend your skills in a new area. Opportunities for a promotion will be reviewed in the normal course of business, aligned with our promotion process.
Equal Opportunity Employer:
NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification.
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Why You'll Thrive at NetApp
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Learn moreNetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification. We pledge to take every reasonable step to ensure that our applicants and employees are respected, treated fairly, and with dignity. See the EEO poster. NetApp makes reasonable accommodations, consistent with applicable laws, for religious purposes and for the known physical or mental limitations of an otherwise qualified applicant or employee with a disability, who can perform the essential job functions unless undue hardship would result.
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