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Data QA Engineer with EXP (AI, Oracle, AWS & ETL Testing) -- W2

Resource Innovative Technologies LLCCharlotte, NC🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationCharlotte, NC, United States
OracleSQLAWSETLSnowflakeDatabricksPostmanPythonRedshiftJiraAgileData Analysis

Job description

Role: Data QA Engineer with EXP (AI, Oracle, AWS & ETL Testing) -- W2
Location: Charlotte, NC / Atlanta, GA / St. Louis, MO
Duration: Long Term
Role Summary
We are seeking an experienced AI/Data QA Engineer with strong expertise in data validation, data quality testing, and Oracle-to-AWS data migration validation. The ideal candidate will be responsible for validating data migrated from Oracle databases to Amazon S3, ensuring data accuracy, completeness, and integrity across data pipelines and reporting systems. Experience leveraging AI tools for anomaly detection, test automation, and quality improvement is highly preferred.
Key Skills
Data Validation | Data Quality | Oracle | Amazon S3 | SQL | ETL Testing | Data Reconciliation | Data Migration Testing | AWS | Glue | Athena | Redshift | AI-Assisted Testing | Python | API Testing | JIRA
Key Responsibilities
Validate data migrated from Oracle databases to Amazon S3.
Perform source-to-target reconciliation and data quality validation.
Develop and execute test plans, test cases, and validation scripts.
Validate ETL/ELT processes, data transformations, and business rules.
Perform SQL-based data analysis and defect investigation.
Identify and resolve data quality issues and anomalies.
Validate APIs, data integrations, reports, and dashboards.
Leverage AI tools to improve testing efficiency and data quality.
Support UAT, defect triage, and production validation activities.
Required Qualifications
10+ years of experience in Data QA, Data Validation, or Data Quality Engineering.
Strong experience with Oracle databases, SQL, and Amazon S3.
Hands-on experience with data reconciliation, ETL testing, and migration validation.
Experience validating large datasets across cloud and on-prem environments.
Knowledge of AWS data services such as S3, Glue, Athena, or Redshift.
Familiarity with AI/ML concepts and AI-assisted testing tools.
Experience with Agile methodologies and defect tracking tools such as JIRA.
Strong analytical, troubleshooting, and communication skills.
Preferred Skills
Python scripting for automation and data validation.
Snowflake, Databricks, or other cloud data platforms.
API testing using Postman or similar tools.
Telecom domain experience is a plus.
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