ETL QA Lead Tester

Role: ETL QA Tester

Location: 100% in Charlotte NC (3 days on site/2 days remote)

Duration: 12 months

MUST HAVE:

12 years total experience 2 years lead experience

Strong ETL/ELT Testing

SSIS

Azure Data Factory

A Data Quality Assurance Lead will assist in data improvement initiatives across the organization. They will work closely with data engineering data analytics and other crossfunctional 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 cloudbased data infrastructure. They will assist in multiyear 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 crossfunctional teams to deliver reliable highquality data solutions that support our business objectives.

Key responsibilities for this role include but are not limited to the following:

Engage across key CircleK stakeholders & data engineering team to determine the data required to deliver the final data product understand the data workflow and review endtoend data journey.

Challenge the status quo and provide an innovative way of thinking for outofthebox 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 Global CircleK 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 enhancements.

Data Management:

Passion and interest in Data Quality with demonstrated precision and attentiontodetail in solving problems

Handson experience using Data Quality tracking tools.

Understanding of data management concepts and associated business processes and tools specifically Data Modelling and Data Quality.

Deliver business performance improvement through addressing data quality.

Process Improvement

Collaborate with Product owner & development teams to define test cases for user stories and oversee their execution.

Ability to optimize data processes to simplify collection and use of data while maintaining data quality.

Comfortable in an agile operating environment. Demonstrates persistence and commitment in implementing product and process improvements.

Analysis focused; identify solutions lead the implementation and help team overcome resistance and obstacles.

Conduct root cause analysis of defects and collaborate with the development team to prevent future occurrences.

Focus on outcomes based on clear KPIs

Leadership & collaboration

Build enduring relationships with internal stakeholders

Manage and mentor a team of QA engineers. Foster a culture of continuous improvement knowledge sharing and innovation within the QA team.

Effectively empower team peers

Work closely with Data Engineers BI developers and product owners to understand requirements identify data quality challenges and ensure the delivery of highquality data products.

Natural change agent with entrepreneurial instincts who articulates the need for change and improvement with ease.

Qualifications

Experience working with business stakeholders and/or product owners to understand data requirements and business cases.

Bachelors degree in Computer Science Information Systems or a related field.

Minimum of 12 years of experience as a QA/Tester with a focus on datacentric projects with at least 2 years in a lead role.

Strong and extensive handson experience in ETL/ELT testing providing DQ reports and performance tuning using ETL tools such as SSIS/ADF in a multidimensional Data Warehousing environment like SQL DB/Synapse.

Handson experience in Azure preferably data heavy / analytics applications leveraging relational and NoSQL databases Data Warehouse and Power BI.

Familiarity with Azure Data Factory Azure Synapse Analytics Azure Analysis Services Azure Databricks Blob Storage Python/PySpark Logic Apps Key Vault and Azure functions and Power BI.

Good experience in defining and enabling data quality standards for auditing and monitoring purposes.

Strong understanding of data engineering concepts including data modeling ETL processes and database management.

Proficiency in SQL and data querying for test validation and analysis.

Strong proficiency in scripting to read/write SQL queries and python.

Strong knowledge of data management ETL processes data warehousing and BI tools.

Professional data management qualifications preferable

Proficiency in the functional and nonfunctional testing including unittesting integration testing and defect management tools.

A great team member with an ability to adapt to change quickly and balance multiple priorities is crucial.

The candidate should be highly organized and efficient with a strong attention to detail and excellent communication skills (both verbal and written).

Experienced in data quality testing for data engineering pipelines and working with data engineering teams is a must.

Strong understanding of Agile methodologies with working experience in Scrum or SAFe Agile frameworks.

Experience with QA automation tools and frameworks is a. plus.

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

Selfstarter with ability to meet tight deadlines and manage multiple competing priorities

Strong attention to detail in their work communication and planning

Proactive problemsolving abilities

Experienced in multifunctions and multiyears implementation or transformation initiatives

Comfortable in engaging at very Senior Level as well as a very detailed/analytical level

Intellectually curious innovative open minded and creative problem solver with impeccable judgement

Knowledgeable about industry data compliance strategies and practices such as continuous integration regression testing and versioning.

Strong collaboration teamwork skills excellent written and verbal communications skills.

Selfstarter and motivated with ability to work in a fastpaced agile environment.

Preferred Qualifications:

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 datarelated services.