Short JD / Mandatory skills: particularly the hands-on Data Warehouse/ETL testing, advanced SQL, Snowflake, and relevant Python-based data automation experience expected for this role

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Detailed JD

Automation Test Lead

We are looking for a highly skilled Automation Test Lead with strong hands-on experience in Data Warehouse, ETL/ELT and Data Platform testing. The candidate should have proven expertise in Python-based test automation framework development, advanced SQL and data validation, along with experience leading testing initiatives and guiding technical solutions.

The idóneo candidate should be able to design, build, enhance and maintain scalable automation frameworks for complex data-testing requirements and work closely with Data Engineers, Architects and other technical teams.

Key Responsibilities

- Data & ETL Testing

- Lead end-to-end testing of Data Warehouse, ETL/ELT and data integration pipelines.
- Validate data flow across source, staging, transformation and target layers.
- Design and execute source-to-target validation, data reconciliation and transformation testing.
- Validate full, incremental and delta data loads.
- Perform testing of large-volume datasets and complex data scenarios.
- Identify data integrity, completeness, duplication and transformation issues.

2. Test Automation Framework Development
- Design, develop and maintain Python-based test automation frameworks and reusable libraries for data validation.
- Enhance existing automation frameworks to support evolving business and technical requirements.
- Develop reusable utilities for data comparison, reconciliation, validation and reporting.
- Apply automation framework best practices, including modularity, maintainability, scalability and exception handling.




- Evaluate opportunities to improve automation coverage and reduce manual validation effort.

3. Advanced SQL & Data Validation
- Develop complex SQL queries for data validation and reconciliation.
- Perform validation using complex joins, CTEs, subqueries, aggregations and window functions.
- Troubleshoot SQL and data-related issues and perform root-cause analysis.
- Develop scenario-specific SQL validation strategies.
- Perform validation across large datasets with focus on performance and accuracy.

4. Snowflake & Data Platforms
- Perform hands-on testing and validation in Snowflake or similar cloud data platforms.
- Validate data across different layers of modern data architectures.
- Understand data warehouse concepts, dimensional modelling and data transformation.
- Validate data migration, transformation and reconciliation scenarios.

5. Data Quality & Reconciliation
- Implement data quality validation covering:
- Accuracy
- Completeness
- Uniqueness
- Consistency
- Referential integrity
- Develop automated source-to-target and cross-system reconciliation mechanisms.
- Identify and prevent data-quality issues early in the delivery lifecycle.

6. CI/CD & DevOps
- Integrate automated data tests into CI/CD pipelines.
- Work with Git-based development workflows, including branching, pull requests and code reviews.
- Implement automated test execution as part of build/release pipelines.




- Support parallel and selective test execution where applicable.
- Ensure automation follows appropriate code quality and engineering practices.

7. Automation Quality & Engineering Practices
- Follow automation framework design and coding best practices.
- Implement appropriate logging, reporting, error handling and reusable components.
- Use static code analysis/code quality tools such as SonarQube, where applicable.
- Review automation code and provide technical guidance to team members.

8. Test Strategy & Leadership
- Define and implement Data/ETL test strategy and automation approach.
- Lead technical discussions and provide solutions for complex testing challenges.
- Mentor and guide automation/data testing engineers.
- Review test scenarios, automation design and technical implementation.
- Work closely with developers, data engineers, architects and business stakeholders.
- Proactively identify risks and recommend improvements to data quality and testing processes.

Mandatory Skills

- 5+ years of relevant hands-on experience in Data/ETL/DWH Testing and automation
- Strong hands-on Python programming
- Proven experience building or significantly enhancing Python-based automation frameworks
- Strong Advanced SQL skills
- Hands-on ETL/ELT and Data Warehouse testing
- Strong experience in data validation and reconciliation
- Experience with Snowflake or similar data platforms
- Experience with large-volume and incremental data validation
- Good understanding of data warehouse concepts and data modelling
- Experience with Git, pull requests and code collaboration
- Experience with CI/CD pipelines
- Strong Test Lead capabilities, including test strategy, technical guidance and mentoring

📌 Quality Assurance Automation Engineer (España)
🏢 Virtusa
📍 España