Position: Data QA Engineer / Data Quality Analyst
Location: Waco, Dallas, Texas
Department: Data Engineering & Analytics
Experience: 6~8 Years
Employment Type: Contract Position
Type: 3 days working from home
One day at Waco client office
One day at Dallas preferred vendor office ( Needs to coordinate with offshore team)
Retail Client
Job Summary
We are seeking an experienced Data QA Engineer to join our Data Engineering team. The candidate will be responsible for ensuring data accuracy, completeness, consistency, and reliability across enterprise data platforms, including databases, data warehouses, ETL/ELT pipelines, and reporting systems.
The ideal candidate will have strong SQL skills, experience validating complex data transformations, and hands-on expertise in data reconciliation, data quality testing, and automation.
Key Responsibilities
Data Validation & Quality Assurance
Validate data across source systems, staging environments, data warehouses, and reporting layers.
Perform data profiling, data integrity checks, and source-to-target reconciliation.
Identify missing records, duplicates, null values, and data inconsistencies.
Validate business rules, data mappings, and transformation logic.
Ensure data quality standards are maintained across applications.
ETL/ELT & Data Pipeline Testing
Test ETL/ELT processes developed using Azure Data Factory, SSIS, Databricks, or similar tools.
Validate data extraction, transformation, and loading processes.
Perform incremental load, historical load, and regression testing.
Verify data accuracy following migrations and system upgrades.
Investigate data discrepancies and coordinate resolution with Data Engineers.
SQL & Database Testing
Write complex SQL queries for data validation and reconciliation.
Validate stored procedures, views, tables, and transformation logic.
Perform record-count, aggregate, and field-level comparisons.
Test database changes and assess downstream data impacts.
Reporting & Analytics Validation
Validate data used in Power BI reports, dashboards, and enterprise analytics.
Reconcile report results against underlying source systems.
Verify business calculations, KPIs, and reporting logic.
Ensure consistency between operational and analytical data.
Test Automation & Defect Management
Develop reusable SQL scripts and automated data validation frameworks.
Use Python or similar technologies to automate repetitive testing.
Create test plans, test cases, and test execution reports.
Track defects using Jira, Azure DevOps, or equivalent tools.
Collaborate with Data Engineers, Business Analysts, and business stakeholders.
Required Skills
4+ years of experience in Data QA, ETL Testing, or Data Warehouse Testing.
Strong hands-on experience with SQL Server and advanced SQL queries.
Experience with ETL/ELT processes and data warehouse concepts.
Strong understanding of data mapping, transformation, and reconciliation.
Experience testing Azure Data Factory, SSIS, or Databricks pipelines.
Knowledge of data quality dimensions such as accuracy, completeness, consistency, and uniqueness.
Experience with Agile methodologies and defect management tools.
Strong analytical, troubleshooting, and communication skills.
Preferred Qualifications:
Experience with Microsoft Azure, Microsoft Fabric, and Power BI.
Experience in insurance, financial services, or other data-intensive industries.
Key Performance Expectations:
Ensure high accuracy and completeness of enterprise data.
Identify data quality issues before production deployment.
Reduce manual validation through automation.
Improve test coverage across data pipelines and reporting systems.
Collaborate proactively with engineering teams to resolve defects.
Maintain comprehensive test documentation and reconciliation reports.