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

¿Es este el puesto que está buscando? Si es así, siga leyendo para obtener más detalles y no olvide enviar su solicitud hoy mismo. ---- Detailed JD: 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

1. 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. 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 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. 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. xsgfvud 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 #J-18808-Ljbffr

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