Data Quality Assurance Team Lead

5 days ago


Charlotte, North Carolina, United States Progilisys Solutions Full time
About the Role

We are seeking a skilled Data Quality Assurance Lead to play a critical role in improving data quality across our organization. This individual will work closely with data engineering, analytics, and other Agile teams to support the development and migration of data into a modern, cloud-based data infrastructure.

The ideal candidate will lead the QA efforts for data engineering and BI projects, driving best practices and ensuring high standards in data quality and integrity.

Key Responsibilities:
  • Collaborate with key stakeholders and the data engineering team to define data requirements, review data workflows, and ensure the delivery of accurate, high-quality data products.
  • Develop innovative solutions for measuring and improving data quality and performance, challenging existing processes and implementing new standards.
  • Create, design, and execute comprehensive QA strategies for data engineering and BI products, focusing on functional, integration, regression, and performance testing.
  • Act as the primary point of contact for data quality issues across core data domains, ensuring data integrity and consistency throughout the data lifecycle.

The successful candidate will have a strong background in QA/testing with a focus on data-centric projects, including experience with ETL/ELT testing, data quality reporting, and performance tuning using tools like SSIS or Azure Data Factory in a Data Warehousing environment.

They will also be proficient in Azure platforms, including Data Factory, Synapse Analytics, Databricks, Blob Storage, and Power BI, as well as strong Python scripting skills.

Requirements:
  • Bachelor's degree in Computer Science, Information Systems, or a related field.
  • 12+ years of experience in QA/testing with a focus on data-centric projects, including at least 2 years in a lead or managerial role.
  • Extensive hands-on experience in ETL/ELT testing, data quality reporting, and performance tuning using tools like SSIS or Azure Data Factory in a Data Warehousing environment.
  • Proficiency in Azure platforms, including Data Factory, Synapse Analytics, Databricks, Blob Storage, and Power BI, as well as strong Python scripting skills.

We offer a competitive salary range of $130,000 - $160,000 per year, depending on experience.



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