Lead QA Data Engineer
4 months ago
Work with leadership on defining current state and next gen analytics QA/testing solutions and strategies.
Lead validation on projects centered on data ingestion, data modeling, and overall data warehouse design.
Research new technologies and how they can be implemented
Design QA, Regression, and Data Quality strategies for enterprise database, data warehouse systems, and multidimensional cubes.
Set standards for quality assurance and regression testing.
Provide support, mentoring, and guidance to QA Data Engineers and Senior QA Data Engineers.
Document the business requirements, test plans, test cases for all QA testing and Regression testing.
Design and execute test scripts for QA and Regression testing.
Validate transformation rules and metric definitions are correctly implemented within the data warehouse and BI solution.
Write SQL queries to validate data warehouse and OLTP databases are populated correctly with data integrity.
Work collaboratively with project teams to ensure that all defects are understood and prioritized.
Responsible for escalation of defects and issues that are not resolved in a timely manner.
Perform reviews of test plans, test cases, and sql queries used by QA data engineers and Senior QA Data Engineers.
Responsible for the analytics data warehouse, implementing QA design principles and establishing business process best practices.
Develop and support data manual and automated testing of pipelines, data lake, and data warehouse solution along with long term regression of those same models and data pipelines.
Ensure clean data sets / products to product owners, analytics/business intelligence teams and end users.
Define alerting and monitoring of production data sets to ensure data remains robust.
Identify, design, and implement internal process improvements (i.e., automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.).
Cross-functionally supports analytical requests for both internal and external stakeholders.
Work with data and analytics experts to strive for greater functionality in our data systems.
Establish scalable, efficient, automated processes for large scale data analyses, model development, validation, and implementation.
Required Skills:
Bachelor’s degree in Computer Science, Information Systems, or related field
8+ years’ experience working as an analytics engineer, qa data engineer, data scientist, data engineer, or related
Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (GCP experience a plus)
8+ years’ experience hands on development with frameworks such as Python, Java, Scala.
Must have experience with both automated and manual testing of data warehouse and BI solutions.
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