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Data Quality Engineer
Company: Coupa Software
Location: Nationwide, US
Employment Type: Full Time
Date Posted: 08/07/2022
Expire Date: 10/07/2022
Job Categories: Computers, Hardware, Computers, Software, Engineering, Information Technology
Job Description
Data Quality Engineer

Responsibilities:
  • Understand business functionality and test Coupa’s Data related products.
  • Perform thorough Data Analysis: evaluating Data Quality, Test Machine Learning Models & Visualizations, outlier detection and the use of statistical methods to define and monitor valid data ranges.
  • Create test plans, execute test cases – both manually and via automation to test Coupa's data-oriented products, data Integrations.
  • Develop automated tests to validate large data sets across products in Coupa.
  • Collaborate with the product and engineering teams to analyze, debug and resolve issues.
  • Participate in daily stand-ups to stay on top of things and report progress
  • Work closely with Scrum team members to clarify requirements, ensure testability and automatability and provide feedback on design (functional and technical)
  • Analyze the potential impact of the requirement changes, assess risk and be a vocal champion for quality in every phase of the development process.
  • Contribute in increasing test automation coverage
Qualifications & Requirements
  • Strong scripting experience with any of the scripting languages like Python or Ruby
  • Strong working experience in Linux.
  • Strong hands-on experience working with APIs.
  • Excellent communication skills & ability to drive & collaborate with cross teams.
  • Experience working in Agile development processes.
  • Ability to read/write SQL queries is a plus.
  • Hands-on experience working with API automation.

Preferred Qualifications:
  • BS in CS, Economics, Statistics or Mathematics with 3 years of experience in Data Testing.
  • Experience working in enterprise cloud BI, Data Integration projects.
  • Knowledgeable in Predictive Analytics, machine learning trade-offs and model evaluation.
Contact Information
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