QA Lead (Data Engineering) - Modern Data Platform Implementation
Job Summary
Job Description
This role requires a senior QA Lead with extensive experience in quality assurance for data platforms and analytics solutions, particularly Databricks implementations within the healthcare sector. Responsibilities include developing comprehensive QA strategies, establishing testing frameworks and methodologies, leading data migration testing from legacy systems, designing automated testing solutions for data pipelines and analytics workflows, implementing data quality validation, ensuring healthcare compliance, collaborating with cross-functional teams, mentoring QA team members, establishing quality metrics, and driving continuous improvement. The ideal candidate will have a proven track record of leading QA teams for complex data implementations and a strong understanding of data quality principles and healthcare regulations.
Must have:
- Extensive experience in data platform QA
- Databricks platform testing expertise
- Healthcare data quality and compliance knowledge
- Data migration testing experience
- Test automation framework experience
- Leadership and mentorship skills
5 skills required
Job Details
Overview
We are seeking a senior QA Lead with extensive experience in quality assurance for data platforms and analytics solutions. This role requires expertise in testing methodologies for Databricks implementations, with a focus on healthcare data quality and compliance. The ideal candidate will have a proven track record of leading QA teams and establishing robust testing frameworks for modern data platforms.
About the Role
As a QA Lead, you will be responsible for ensuring the quality, reliability, and compliance of Databricks-based Modern Data Platform implementations. You will lead the quality assurance strategy and execution for data migration initiatives from legacy systems, establishing testing frameworks, methodologies, and best practices to ensure successful delivery of high-quality solutions.
Key Responsibilities
Develop and implement comprehensive QA strategies for Databricks or Lakehouse platform implementations
Establish testing frameworks, methodologies, and best practices for data testing Data platform
Lead the testing of Data Warehouse/Data Lake migration processes from legacy systems to Databricks
Design and implement automated testing solutions for data pipelines and analytics workflows
Create and maintain test plans, test cases, and test data for complex data scenarios
Implement data quality validation frameworks and monitoring solutions
Ensure compliance with healthcare industry regulations and data governance requirements
Collaborate with cross-functional teams to integrate quality assurance throughout the development lifecycle
Lead and mentor QA team members, providing technical guidance and career development
Establish metrics and reporting mechanisms to track data quality and testing effectiveness
Identify and mitigate quality risks in data platform implementations
Drive continuous improvement in testing processes and methodologies
Qualifications
Extensive experience in quality assurance for data platforms and analytics solutions
Proven track record of leading QA teams for complex data implementations
Experience with Databricks platform and Lakehouse architecture testing
Strong understanding of data quality principles and methodologies
Experience testing data migrations from legacy systems to modern platforms
Knowledge of healthcare data requirements, regulations, and compliance standards
Experience with test automation frameworks and tools for data solutions
Strong understanding of data engineering and analytics workflows
Experience with Agile testing methodologies
Bachelor's degree in Computer Science, Information Systems, or related field; advanced degree preferred
Professional certifications such as ISTQB, CSTE, or equivalent
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