Data Quality Testing Engineer

QodeSouth Carolina, SC
15h

About The Position

We are seeking a highly skilled and experienced Data Quality Testing Engineer to join our dynamic team. In this role, you will be responsible for ensuring the quality and reliability of our data pipelines and data warehousing solutions built on AWS technologies. You will work closely with data engineers, data scientists, and other stakeholders to develop and execute comprehensive test plans, identify data quality issues, and implement solutions to improve data accuracy and consistency. The ideal candidate will have a strong background in data testing, a deep understanding of AWS services, and excellent problem-solving skills. This is a fantastic opportunity to contribute to a data-driven organization and make a significant impact on our business.

Requirements

  • 10+ years of proven experience as a Data Quality Testing Engineer with a focus on AWS technologies.
  • Strong proficiency in Python, PySpark, SQL, and related data testing technologies.
  • Experience with AWS Lambda, AWS Glue, and Snowflake for data processing and analysis.
  • Familiarity with Selenium for test automation.
  • Knowledge of test management tools such as qTest and pytest.
  • Solid understanding of test automation frameworks.
  • Excellent problem-solving skills and attention to detail.
  • Experience with data warehousing concepts and data modeling techniques.
  • Strong communication and collaboration skills.
  • Bachelor's degree in Computer Science, Engineering, or a related field.

Responsibilities

  • Develop and execute comprehensive test plans and test cases for data pipelines and data warehousing solutions.
  • Utilize AWS Lambda, AWS Glue, and Snowflake to perform data processing and analysis for testing purposes.
  • Design and implement automated tests using Selenium and other test automation frameworks.
  • Manage and maintain test environments and test data.
  • Identify, document, and track data quality issues using test management tools such as qTest and pytest.
  • Collaborate with data engineers and data scientists to resolve data quality issues and improve data accuracy.
  • Participate in code reviews and provide feedback on data engineering code.
  • Contribute to the development of data quality standards and best practices.
  • Monitor data quality metrics and identify trends and anomalies.
  • Communicate test results and data quality issues to stakeholders in a clear and concise manner.
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