Experience : Minimum 6 - 10 Years
Shift : 5PM - 2 AM (US Shift)
Mode of work : REMOTE - Work from Home
Location : Hyderabad Only
Background Verification of the candidates will be done.
Strictly NO moonlighting.
Qualifications : Experience
- 6 - 10+ years in Quality Engineering, particularly in data / ETL testing; leadership in Data Modernization initiatives preferred.
Technical Proficiency
Strong coding skills in SQL, Python, PySpark, Scala, (Java is a plus) for automation and data validations.Strong Expertise in ETL testing, data pipeline frameworks (ingestion, profiling, DataOps) and Unity Catalog.Hands-on Strong experience in Datawarehouse Concepts.Experience in writing numerous test cases.Good understanding of data governance, profiling, ingestion, and data quality validation.Soft Skills
Excellent analytical, problem-solving and communication abilities.Stakeholder management and coordination skills across matrix environments.Self-motivated with proactive mindset.Good to have : Automation & DevOps
Strong knowledge of test automation frameworks, CI / CD (Azure DevOps, Git), and experience integrating test frameworks into pipelines.Key Roles & Responsibilities :
Strategy & Leadership
Develop and implement comprehensive test strategiesLead and mentor QA / testing teams, coaching best practices and maintaining QE documentation.Act as the primary point-of-contact for all data testing activitiesTest Planning & Execution
Plan, design, and oversee test cases across functional, UAT, E2E, and performance domains.Validate ETL pipelines via SQL, Python, PySpark, Scala; ensure data accuracy.Automation & Tooling
Build and maintain automated testing frameworks integrated with CI / CD pipelines.Utilize test automation tools and data validation frameworks like Great Expectations.Use Databricks capabilities such as Delta Live Tables, Unity Catalog, and built-in workflows for monitoring and orchestration.Performance & Quality
Identify performance bottlenecks and guide performance / security testing efforts.Implement data governance, profiling, data ingestion validation, and pipeline monitoring.Documentation & MetricsTrack QE progress, metrics, and communicate risks to stakeholders.Maintain detailed test cases, validation rules, defect logs, and automation artifacts.Collaboration & Stakeholder Management
Coordinate with data engineering, infrastructure, and business teams to resolve issues.Participate in Agile rituals like sprint planning and retrospectives.Optional / Domain-specific Add-ons :
Domain experience (e.g., HealthCare Exp)—bonus.Familiarity with Power BI as ETL visualization tool.Certifications in Azure or Databricks (e.g., Azure Data Engineer, Databricks Associate)Education
Bachelor's or Master's in Computer Science, Engineering, IT, or related
Skills Required
Java, Etl Testing, Scala, Pyspark, Sql, Git, Datawarehouse Concepts, Databricks, Python, Azure Devops