Job Title

I. Job Summary:The Senior QA Data Analytics Engineer will develop and implement strategies for testing, validation, regression, and overall quality assurance of the data layer across the entire analytics stack. This includes data in OLTP databases, data warehouses, BI tools, and OLAP/Cube technologies. The role focuses on ensuring strong, reliable data for critical business decisions by developing mechanisms to measure data quality. The engineer will collaborate with teams across data engineering, analytics, and visualization to deliver robust Business Intelligence solutions.II. Roles & Responsibilities:Collaborate with leadership to define current and next-generation analytics QA/testing solutions and strategies.Lead validation efforts for projects involving data ingestion, modeling, and data warehouse design.Research emerging QA technologies and evaluate their applicability.Design QA, regression, and data quality strategies for enterprise databases, data warehouses, and multidimensional cubes.Establish standards for quality assurance and regression testing.Provide support, mentoring, and guidance to QA Data Engineers.Document business requirements, test plans, and test cases for QA and regression testing.Design and execute test scripts for QA and regression.Validate transformation rules and metric implementations within data warehouses and BI solutions.Write SQL queries to verify data integrity in data warehouses and OLTP databases.Work closely with project teams to understand and prioritize defect resolutions.Develop and support both manual and automated testing for data pipelines, data lakes, and data warehouse solutions, including long-term regression testing.Ensure delivery of clean data sets to product owners, analytics teams, and end users.Define alerting and monitoring systems for production data to maintain data robustness.Identify, design, and implement internal process improvements such as automating manual tasks and optimizing data delivery.Support analytical requests cross-functionally for internal and external stakeholders.Collaborate with data and analytics experts to enhance data system functionalities.Establish scalable, efficient, automated processes for large-scale data analytics, model development, validation, and implementation.III. Years of Experience:Minimum 5 years’ experience as an analytics engineer, QA data engineer, data scientist, data engineer, or related field.IV. Educational Qualification & Certifications (Optional):Bachelor’s degree in Computer Science, Information Systems, or related field.V. Skill Set Required:Must have:Experience developing solutions on cloud computing platforms, preferably GCP.5+ years hands-on development experience with frameworks such as Python, Java, or Scala.Experience with both automated and manual testing of data warehouse and BI solutions.Nice to have:Advanced SQL knowledge and experience with relational databases and complex query authoring.Experience with Scala, Python, PySpark, Java, REST API, Microservices, etc.Experience in restaurant or retail operations preferred but not mandatory.