Job Description - ETL QA Lead Job Title: Quality Engineering Lead
Location: Mexico
Experience: 8-10 Year
Role Summary We are seeking an ETL QA Lead with strong hands-on experience in ETL testing, data validation, SQL, and data warehouse testing. The candidate will be responsible for leading the overall ETL testing strategy and execution, validating source-to-target data flows and transformation rules, driving data quality and reconciliation, mentoring QA team members, managing quality risks, and ensuring accurate and reliable data delivery across ETL pipelines and data platforms.
Key Responsibilities - Analyze Business Requirements Documents (BRD), User Stories, Source-to-Target Mapping documents, and data transformation specifications.
- Lead ETL testing strategy, planning, estimation, execution, and release validation activities.
- Define and review ETL test scenarios, test cases, test data, and SQL validation approaches based on business and technical requirements.
- Lead source-to-target validation and reconciliation, ensuring data completeness, accuracy, consistency, and integrity.
- Validate complex data extraction, transformation, business rules, calculations, aggregations, joins, filters, and loading processes.
- Develop and review complex SQL queries for backend validation, reconciliation, and data quality verification.
- Ensure appropriate validation of full, incremental, delta, and historical data loads, including SCD validation.
- Lead testing of ETL workflows, batch jobs, scheduled jobs, dependencies, and end-to-end data pipelines.
- Review test execution results, reconciliation reports, defects, and data quality findings and drive issues to closure.
- Guide and mentor QA team members, review testing deliverables, and ensure adherence to testing standards and best practices.
- Identify quality risks, dependencies, test coverage gaps, and data issues and define appropriate mitigation plans.
- Represent QA in requirement reviews, sprint/release planning, defect triage, release-readiness, and stakeholder discussions.
- Collaborate with Data Engineers, Developers, Business Analysts, Data Architects, Product Owners, DevOps teams, and Project Managers.
- Provide stakeholders with test execution status, data quality metrics, defect trends, risks, and release-readiness updates.
Required Skills - Strong hands-on experience in ETL Testing, Data Validation, and Data Warehouse Testing.
- Strong expertise in SQL, including joins, subqueries, CTEs, aggregate functions, and analytical/window functions.
- Strong experience in source-to-target validation, data reconciliation, and transformation rule validation.
- Experience in leading ETL/Data QA teams and testing initiatives.
- Strong understanding of ETL processes, data pipelines, data warehouses, and data integration architecture.
- Experience with data completeness, accuracy, integrity, duplicate, NULL, referential integrity, and reconciliation testing.
- Strong understanding of fact tables, dimension tables, primary/foreign keys, and Slowly Changing Dimensions (SCD Type 1 and Type 2).
- Experience validating full, incremental, delta, and historical data loads.
- Experience with databases/data platforms such as SQL Server, Oracle, PostgreSQL, Snowflake, or similar technologies.
- Experience with ETL/data integration technologies such as Informatica, Talend, SSIS, DataStage, Azure Data Factory, or similar tools.
- Experience with test estimation, resource planning, defect management, risk management, and quality reporting.
- Strong understanding of SDLC, STLC, Agile/Scrum, and defect lifecycle management.
- Strong leadership, mentoring, stakeholder management, analytical, troubleshooting, and communication skills.
Preferred Skills - Experience with cloud data platforms such as Snowflake, GCP, Azure Synapse Analytics, Databricks, or AWS Redshift.
- Experience with cloud-based ETL and data integration platforms.
- Knowledge of Python and Unix/Linux for data validation and test automation.
- Experience with ETL test automation and automated data reconciliation frameworks.
- Experience testing large-volume datasets and complex data pipelines.
- Knowledge of data quality frameworks, metadata validation, and data lineage.
- Experience with different data formats including CSV, JSON, XML, Parquet, and flat files.
- Knowledge of CI/CD and version control using Git, Jenkins, Azure DevOps, or GitHub Actions.
- Experience supporting UAT, production validation, post-production reconciliation, and release readiness.
- Ability to communicate in Spanish is preferred for Mexico client engagements.
Key Deliverables - ETL Test Strategy and Test Plan
- Source-to-Target Validation Approach and Test Cases
- SQL Validation and Reconciliation Scripts
- ETL Test Execution and Data Quality Reports
- Defect Reports and Traceability Matrix
- Test Coverage, Defect, and Quality Metrics
- Data Load and Reconciliation Reports
- Quality Risk and Release Readiness Assessment
- UAT/Production Validation Support
- Test Closure Report
