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