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Enterprise Software, Cloud Computing, Data Storage

Software Engineer, Customer Success

CaliforniaOnsiteFull Time$196,350–$292,600 /yrPosted 1 month agoVisa sponsorship available

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Required skills

  • workload assets
  • automation tools
  • product validation
  • product support
  • synthetic workload queries
  • datasets
  • analysis tools
  • diagnostic tools
  • log analysis
  • root cause analysis

Nice to have

  • GenAI preprocessing
  • hardware-accelerated computing
  • parallel processing
  • compilers
  • machine learning
  • cloud-native computing

Role summary

DataPelago is seeking a Software Engineer for Customer Success to develop workload assets and automation tools for product validation and support. This role involves applying AI to proactively identify and resolve issues in their data processing engine, which accelerates Apache Spark, Apache Flink, and Ray. Responsibilities include creating test data, developing diagnostic tools for Spark and related environments, handling customer support issues, conducting product validation, and analyzing test results to identify bugs and tuning opportunities. The ideal candidate has a Bachelor's degree in computer science, 12+ years of experience in data processing software, 2+ years in customer support, and 2+ years supporting Apache Spark pipelines.

Job Summary

DataPelago is at the forefront of revolutionizing data processing for traditional analytics and cutting-edge GenAI preprocessing. We are building an innovative data processing engine that is transforming how Apache Spark, Apache Flink, Ray and others operate on diverse, large-scale data. Our team of engineers drive and adopt advances in hardware-accelerated computing, parallel processing of large-scale data, query optimization, distributed systems, compilers, machine learning, and cloud-native computing. We are looking for specialists to join our engineering team and shape the future of accelerated data processing.

DataPelago Nucleus is a universal data processing engine that is designed to accelerate the processing of diverse data – structured through unstructured – with any parallel processing framework – e.g., Apache Spark – on any infrastructure – including vectorized CPU and GPU. DataPelago Accelerator for Spark (DPA-S), our product based on DataPelago Nucleus, is running large-scale production applications of many globally renowned customers.

The Opportunity:

 

As a 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.

What You'll Do:

  • 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:

  • Bachelor’s degree in computer science or a related field.
  • 12+ years of experience related to development, validation and support of enterprise data processing software products.
  • 2+ years of experience providing direct support to external customers.
  • 2+ 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.

Compensation:
The target salary range for this position is 196,350 - 292,600 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU’s), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process. 

Sample NetApp interview questions

  • 1

    How do you figure out what’s causing a server to use too much CPU?

    technicalmedium
  • 2

    Find the majority element in an array. Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊n / 2⌋ times. You may assume that the majority element always exists in the array. Input: nums = [3, 2, 3] Output: 3 Explanation: The number 3 appears 2 times, which is strictly greater than n/2 (1.5).

    codingmedium
  • 3

    Maximum Depth of an N-ary Tree Find the maximum depth of an N-ary tree. Input: root = [1,null,2,null,3,null,4] Output: 4 Explanation: The tree is essentially a straight line, requiring a traversal that reaches a maximum depth of 4 layers.

    codingmedium
  • 4

    Lowest Common Ancestor on an N-ary Tree Find the lowest common ancestor on an N-ary tree. Input: root = [1,null,2,3,4], p = 2, q = 3 Output: 1 Explanation: Both nodes 2 and 3 are direct children of the root node 1, making 1 the lowest common ancestor.

    codingmedium
  • 5

    Maximum Subarray Sum Find the maximum subarray sum in an integer array. Input: nums = [-3,-4,-1,-2] Output: -1 Explanation: Kadane's algorithm correctly identifies that the single isolated element -1 provides the highest possible sum.

    codingmedium

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