Data QA : Raleigh, NC (Onsite)

Job Title:

Data QA Location:

Raleigh, NC Key Responsibilities Design & execute test plans for ETL/ELT workflows, data feeds, and batch extracts, ensuring comprehensive data validation Write and maintain manual and automated tests for data accuracy, completeness, and consistency against mapping documents and specification rules Develop SQL-based validation logic -supporting complex queries, joins, aggregates, and stored procedures-to verify data correctness Collaborate with data engineering, BI, architecture teams to identify and resolve data quality issues across data pipelines Develop or support CI/CD pipelines for automated data quality checks and data-flow validations Analyze test results, document defects, track resolution, and report status to stakeholders; act as advocate for quality in an Agile delivery process Required Skills & Experience Bachelor s or Master s degree in Computer Science, Engineering, or related field 5-6+ years of experience in QA, SDET, or data quality roles-preferably in data engineering/test test automation in the financial services industry Strong programming and automation experience in Python or Java , with focus on testing frameworks and automation tools (e.g. Selenium, TestNG, Appium) Advanced SQL skills , capable of building complex queries to validate ETL, data loads, and data transformations Handson with ETL/Database testing -manual & automated-covering batch pipelines, API integrations, and data feeds Experience with AWS-based data environments (e.g. S3, RDS, DynamoDB, Lambda, Snowflake, Redshift) and familiar in working with data lakes Knowledge of CI/CD tools (Jenkins, TeamCity, GitHub Actions, Octopus), test automation in pipelines, and Agile methodologies including Scrum ceremonies Preferred Qualifications Familiarity with data quality tools , metrics frameworks, rule validation engines, or profiling platforms Exposure to big data technologies -such as Hadoop, Snowflake, DBT, Kafka, DBT, Airflow, FiveTran, PySpark-for data testing contexts Understanding of dimension modeling (star schema, SCD), data governance standards, metadata management, and change data capture patterns Financial services domain experience and familiarity with regulatory/operational compliance testing contexts