Quality Assurance Manager

Job Title: Data Quality Assurance LeadLocation: Charlotte, NC (3 days in-office)Rate: Up to $65 per hourSector: RetailEmployment Type: Contract-to-HireThe Data Quality Assurance Lead will drive data quality initiatives, collaborating with data engineering, analytics, and cross-functional Agile teams. The role includes supporting data lineage, defining critical data elements, and managing data migration to a modern cloud infrastructure. This position will contribute to long-term initiatives focused on digital transformation.This is a brand new role and you will be given the opportunity to grow a team up from scratch to approximately 4-6 staff. The role will be 75% hands-on and 25% team management.Key Responsibilities:Collaborate with stakeholders and data engineering to define data requirements, understand workflows, and review the end-to-end data novate and implement new data quality and performance metrics, challenging existing processes.Develop QA strategies for data engineering and BI products, ensuring data accuracy, completeness, and reliability.Lead functional, integration, regression, and performance testing to ensure data quality.Serve as the main contact for data quality within relevant data domains, and contribute to standardizing data requirements across workflows.Design and monitor key performance indicators (KPIs) related to data processes and quality.Identify process improvements and implement automation tools to enhance efficiency.Liaise between QA, development, and business teams to ensure alignment on project goals and quality expectations.Monitor and improve process performance, suggesting data quality enhancements.Required Experience:Bachelor's degree in Computer Science, Information Systems, or a related field.12+ years of QAtesting experience, with 2+ years in a lead role on data-centric projects.Strong hands-on experience with ETLELT testing, data quality reporting, and performance tuning, especially with SSIS or Azure Data Factory in a multidimensional data warehousing environment.Expertise with Azure-based solutions, including Synapse, Databricks, Power BI, SQL, and PythonPySpark.Proficiency in defining data quality standards and monitoring data processes.Strong knowledge of data engineering concepts, including ETL, data modeling, and database management.

Created: 2024-10-27