Data Quality Assurance (QA) Engineer – P&C Insurance
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Job Location:
Cincinnati, OH - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
Job Title: Data Quality Assurance (QA) Engineer P&C Insurance
Location: Cincinnati OH (Hybrid / Onsite)
Employment Type: Contract
Experience: 8 Years
Location: Cincinnati OH (Hybrid / Onsite)
Employment Type: Contract
Experience: 8 Years
Job Summary
We are seeking a Data QA Engineer with Property & Casualty (P&C) Insurance experience to ensure the accuracy integrity and reliability of enterprise insurance data across policy claims underwriting billing and actuarial systems. This role plays a critical part in validating data pipelines and supporting trusted analytics regulatory reporting and operational decision-making.
We are seeking a Data QA Engineer with Property & Casualty (P&C) Insurance experience to ensure the accuracy integrity and reliability of enterprise insurance data across policy claims underwriting billing and actuarial systems. This role plays a critical part in validating data pipelines and supporting trusted analytics regulatory reporting and operational decision-making.
The ideal candidate will have hands-on experience validating insurance data flows and working closely with Data Engineering Business Analysts and Data Governance teams in a regulated insurance environment.
Key Responsibilities
Validate data ingestion transformation and consumption across P&C insurance domains
Design and execute data quality test plans for data warehouses data lakes and reporting platforms
Perform source-to-target validation reconciliation and business rule testing for insurance data
Validate premium exposure loss reserve and claims transaction data
Identify data defects analyze root causes and collaborate with engineering teams for resolution
Develop automated data validation scripts and regression tests
Support UAT and production data validation for releases and enhancements
Monitor and report data quality metrics KPIs and thresholds
Ensure compliance with insurance regulatory and internal data standards
Participate in data governance and data quality initiatives
Validate data ingestion transformation and consumption across P&C insurance domains
Design and execute data quality test plans for data warehouses data lakes and reporting platforms
Perform source-to-target validation reconciliation and business rule testing for insurance data
Validate premium exposure loss reserve and claims transaction data
Identify data defects analyze root causes and collaborate with engineering teams for resolution
Develop automated data validation scripts and regression tests
Support UAT and production data validation for releases and enhancements
Monitor and report data quality metrics KPIs and thresholds
Ensure compliance with insurance regulatory and internal data standards
Participate in data governance and data quality initiatives
Required Qualifications
5 years of experience in Data QA / Data Quality Engineering
Strong experience working in P&C Insurance data environments
Advanced SQL skills for data analysis and validation
Experience validating ETL/ELT pipelines using tools such as Informatica or similar
Strong understanding of insurance data models and terminology:
Policy lifecycle endorsements renewals
Claims lifecycle reserves subrogation recoveries
Premiums exposures losses loss ratios
Experience with data warehouses and cloud platforms (Snowflake Redshift Azure Synapse SQL Server Oracle)
Familiarity with data quality dimensions (accuracy completeness timeliness consistency)
5 years of experience in Data QA / Data Quality Engineering
Strong experience working in P&C Insurance data environments
Advanced SQL skills for data analysis and validation
Experience validating ETL/ELT pipelines using tools such as Informatica or similar
Strong understanding of insurance data models and terminology:
Policy lifecycle endorsements renewals
Claims lifecycle reserves subrogation recoveries
Premiums exposures losses loss ratios
Experience with data warehouses and cloud platforms (Snowflake Redshift Azure Synapse SQL Server Oracle)
Familiarity with data quality dimensions (accuracy completeness timeliness consistency)
Preferred / Nice-to-Have Skills
Experience with data quality and observability tools (Informatica DQ Collibra DQ)
Knowledge of Agile/Scrum methodologies
Cloud experience in AWS or Azure insurance data platforms
Experience with data quality and observability tools (Informatica DQ Collibra DQ)
Knowledge of Agile/Scrum methodologies
Cloud experience in AWS or Azure insurance data platforms
Education
Bachelors degree in Computer Science Information Systems Engineering or equivalent experience.
Bachelors degree in Computer Science Information Systems Engineering or equivalent experience.
Key Skills
- Test Cases
- Performance Testing
- Quality Assurance
- SOC
- Agile
- Debugging
- Jira
- Perl
- Software Testing
- Test Automation
- Scripting
- Selenium
