Job Details

ID #52475728
Estado Carolina del Norte
Ciudad Charlotte
Full-time
Salario USD TBD TBD
Fuente Insight Global
Showed 2024-09-09
Fecha 2024-09-10
Fecha tope 2024-11-08
Categoría Etcétera
Crear un currículum vítae
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Data Quality Assurance Lead - Hybrid in Charlotte, NC

Carolina del Norte, Charlotte, 28201 Charlotte USA
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Job DescriptionOur client is looking for a Exclusive Data Quality Assurance Lead to join their team. The Data Quality Assurance Lead will assist in data improvement initiatives across the organization. They will work closely with data engineering, data analytics and other cross-functional teams that adopt Agile operating methods. They will support the creation of data lineage flows, participate in designing data taxonomies, help define data elements and support data migration into a modern, cloud-based data infrastructure. They will assist in multi-year initiatives that transform processes to enable digitalization. A successful candidate will have a diverse skillset, be proactive, and have strong analytical and technical skills. The ideal candidate will lead the QA efforts for data engineering and BI projects, driving best practices, and collaborating with cross-functional teams to deliver reliable, high-quality data solutions that support our business objectives. Additional responsibilities of this individual are shown below: Engage across key the clients stakeholders & data engineering team to determine the data required to deliver the final data product, understand the data workflow, and review end-to-end data journey Challenge the status quo and provide an innovative way of thinking for out-of-the-box data quality and data performance metrics Develop and implement comprehensive QA strategies and plans for data engineering and BI products Design, develop, and execute test plans, including functional, integration, regression, and performance testing, to ensure the accuracy, completeness, and reliability of data products Be the key point of contact for relevant Core and/or functional data domains data quality Contribute to initial set of harmonized data requirements across the workflow contributing to efficiency and quality enhancements Responsible for data definitions, critical to quality, across relevant stakeholders Design and monitor key performance indicators related to key data processes and data quality for the clients Data Platform. Identify opportunities for process improvements within the QA and data engineering processes. Implement automation tools and techniques to enhance efficiency and effectiveness Act as a liaison between QA, development, and business teams to ensure alignment and understanding of project goals and quality expectations Monitor and report on observed process performance & suggest data quality enhancementsWe are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] .   To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/ .Skills and Requirements11+ years of experience as a QA/Tester 6+ years of most recent QA experience focused on data-centric projects Minimum of 2 years of experience working in a lead roleo Experience working with business stakeholders and/or product owners to understand data requirements and business caseso Experience of having Quality Data Analysts reporting into you Proficiency in SQL and data querying for test validation and analysis Strong knowledge of data management, ETL processes, data warehousing, and BI tools Experienced in data quality testing for data engineering pipelines and working with data engineering teams Strong understanding of Agile methodologies, with working experience in Scrum or SAFe Agile frameworks Established track record of working with Technology (including experience with APIs) and agile methodology Demonstratable experience handling large amount of data, bringing order and rigor to unstructured data environments and enhancing accuracy Experienced in multi-functions and multi-years implementation or transformation initiatives Bachelors degree in Computer Science, Information Systems, or a related field Experience in the retail industry, with knowledge of retail operations Certification in Quality Assurance, Data Engineering, or related fields Familiarity with cloud platforms (e.g., Azure) and their data-related services Experience with QA automation tools and frameworks Preferred - test the data and pipelines on Azure Databricks Professional data management qualifications preferable nullWe are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal employment opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion,sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military oruniformed service member status, or any other status or characteristic protected by applicable laws, regulations, andordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to [email protected].

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