QA ETL Testing

Matrix Global

. Design, develop, and execute test plans, test cases, and test scenarios for ETL/ELT pipelines and data integration workflows .

Posted 10/16/2026full-timeJacksonville • Florida • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in ETL Testing, Data Validation, and Data Warehouse Testing, with strong proficiency in SQL and a solid understanding of data warehousing concepts. Capable of collaborating effectively with cross-functional teams to ensure high-quality data delivery and improve testing processes.

Highest-signal resume keywords

ETL TestingSQL ProficiencyData Warehouse TestingData ValidationData Quality Assurance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLData ValidationETL/ELT TestingData MappingData TransformationData Quality FrameworksData Integration LogicComplex SQL QueriesData ReconciliationDimensional Modeling

Soft Skills

Analytical SkillsProblem-SolvingAttention to DetailCollaborationCommunication

Tools & Technologies

SQL ServerOracleSSISInformaticaTalendAzure Data FactoryAWS GlueSnowflakePower BITableau

Industry Keywords

BankingFinancial ServicesPaymentsData WarehousingAgileScrumCI/CD PracticesAutomated TestingData-Intensive IndustriesDistributed Processing Systems

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureCloudETLInformaticaOracleSeleniumSQLSSISTableau

About the role

Key responsibilities & impact

Design, develop, and execute test plans, test cases, and test scenarios for ETL/ELT pipelines and data integration workflows
Validate data extraction, transformation, and loading processes across source systems, staging environments, data warehouses, and target systems
Perform source-to-target data validation for accuracy, completeness, consistency, and integrity
Write complex SQL queries to verify transformations, perform reconciliations, and identify discrepancies
Test data mappings, transformation logic, business rules, aggregations, calculations, and derived fields
Validate data quality across large datasets, including duplicates, missing values, incorrect formats, null values, and referential integrity issues
Test incremental loads, full loads, historical data loads, and CDC processes where applicable
Perform backend testing for data warehouses, data marts, and analytical reporting solutions
Validate BI reports and dashboards against underlying source data and business requirements
Collaborate with data engineers and developers to investigate defects, identify root causes, and verify fixes
Create and maintain test data, test scripts, test evidence, defect reports, and test execution documentation
Support regression, integration, system, and user acceptance testing
Improve data testing processes, reusable validation scripts, and test automation
Work closely with data engineers, business analysts, and QA teams to ensure high-quality data delivery for reporting and analytics

Requirements

What you’ll need

5+ years of experience in ETL testing, data warehouse testing, data validation, or database testing
Strong proficiency in SQL, including complex joins, subqueries, CTEs, aggregations, window functions, and data reconciliation queries
Hands-on experience testing ETL/ELT pipelines and validating source-to-target data flows
Strong understanding of data warehousing concepts, dimensional modeling, fact and dimension tables, and star/snowflake schemas
Experience validating data transformations, business rules, data mappings, and data integration logic
Familiarity with relational databases such as SQL Server, Oracle, or similar platforms
Experience identifying, documenting, tracking, and retesting data-related defects
Strong analytical and problem-solving skills, with attention to detail and the ability to investigate complex data issues
Ability to work collaboratively with data engineering, QA, analytics, and business teams
Experience with several of: Advanced SQL, SQL Server, Oracle, SSIS, Informatica, Talend, Azure Data Factory, AWS Glue, Snowflake, Azure Synapse, Amazon Redshift, Power BI, Tableau, Selenium, Playwright, Jira, or Azure DevOps
Nice to have: experience testing cloud-based data platforms and modern data pipelines
Nice to have: familiarity with data quality frameworks, automated reconciliation, and anomaly detection
Nice to have: experience validating APIs or data feeds that integrate with ETL workflows
Nice to have: knowledge of CI/CD practices and automated testing within data engineering environments
Nice to have: experience testing large-scale datasets and distributed processing systems
Nice to have: familiarity with Agile/Scrum methodologies and standard QA processes
Nice to have: experience in banking, financial services, payments, or other data-intensive industries

Benefits

Comp & perks

Competitive compensation and benefits
Meaningful career development opportunities
Diverse, inclusive culture
Collaboration, continuous learning, and growth