Here at Discount Tire, we celebrate the spirit of our people with extraordinary pride and enthusiasm. Our business has been growing for more than 55 years and now is the best time in our history to join us. We recognize that to remain the industry leader we must continue to grow and evolve our business in a rapidly changing industry. We are achieving this, not only by opening new stores, but by transforming our technological landscape and making data a central component of our strategy. The Business Analytics team, one of the fastest growing teams in the company, is leading this change. We are responsible for driving the insights, recommendations, and developing the decision support tools that influence the strategic direction of the company.
The Data Solutions QA Engineer performs validations of the various components of the Analytics environment including but not limited to, the data lake, enterprise data warehouse and BI Applications. Ensures the accuracy of data flowing through each stage of the development process, fulfillment of requirements including adherence to the Company's Business Intelligence (BI) guidelines.
Essential Duties and Responsibilities:
- Conduct end-to-end QA delivery of data platform, enterprise data warehouse, data/data science solutions, business intelligence solutions including, but not limited to, reports, dashboards and mobile applications.
- Work with Data Engineers and Data Scientists to develop automated scripted tools (i.e.: Python, R, Bash) to test and validate data science models, data and pipelines.
- Define, execute and evangelizes testing frameworks and testing strategy
- Work with BI developers to test reports, dashboards and mobile applications, using both manual and automated methods
- Perform, document and maintain functional, regression, integration, and acceptance testing
- Identify risks to inform resource allocation, prioritization, and target areas for automated coverage and ongoing monitoring
- Collaborate with data engineers, BI developers and data scientists to identify, document, resolve defects
- Define and implement monitoring solutions for production environments
- Help drive automation of regression and integration testing across entire data environment
- Collaborate with team members in code reviews, discovering better practices and patterns and continuous improvements
- Stay current with QA best practices, methodologies and technologies, and continue to improve the QA processes across the team
- Innovate constantly and maintain the technical edge
- Assists employees, vendors or other customers by answering questions related to analytics quality processes, procedures and services
- Completes work in a timely and accurate manner while providing exceptional customer service
- Other duties as assigned
- 3 years of big data/ business intelligence / data engineer QA Engineer or Developer experience
- BS/BA Computer Science, Mathematics, Statistics, Engineering or equivalent technical training
- Proven experience designing and implementing automated testing solutions is essential.
- Understanding of data lake/ big data concepts required
- Experience with data warehouse tools (Teradata, Oracle, Netezza, SQL, NoSQL etc.) as well as cloud-based data warehouse tools (Snowflake, Redshift, AWS Athena, AWS Dynamo DB, Google BigQuery) is required
- Experience with ETL/ELT tools such as Matillion, Informatica, AWS GLUE and understands the pros/cons of transforming data in ETL or ELT fashion required.
- Good understanding of data warehouse concepts of schemas, tables, views, materialized views, stored procedures, and roles/security is required
- Adept at building processes to support data transformation, data structures, metadata, dependency and workload management preferred
- Experience with BI tools such Tableau, PowerBI, Cognos and Microstrategy
- Advanced to expert level experience SQL/TSQL is required
- Proven scripting ability in Python, R, or Bash is required
- Advanced experience with various file format such as XML, JSON, CSV, or Text is required
- Experience with automated scheduling tools such as Skybot, Contol-M, or Unix Cron is preferred
- Familiarity with statistical modeling concepts is preferred
- Experience with cloud technologies like AWS, Azure, or Google Cloud is preferred
- Experience with UI/UX automated testing tools such as Selenium and Appian is nice to have.
- Experience with various integration techniques, such as streaming, CDC, bulk loading, is helpful.
- Understanding of the Testing Life Cycle fundamentals is necessary
- Experience with the review of requirements documents, risk analysis and specification documents is necessary
- Understanding of Functional, Non Functional, System Integration and Regression testing principles is essential
- Ability to write, execute and validate manual and automated scripts and relational database queries is required
- Knowledge of defect management tools is necessary
- Knowledge of change management source control tools such as SVN, Git is necessary
- Agile experience is preferred
- This position requires Bachelor's Degree in Computer Science, Engineering or equivalent technical training.
- ISTQB or CSTE Foundation Certification preferred.
Normal work days are Monday through Friday. Occasional Saturdays and Sundays may be necessary.
Normal work hours are 8:00 a.m. to 5:00 p.m. Additional hours may be necessary.