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Posted: 10/20/2026Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data quality management, data governance, and validation practices, with a strong focus on root cause analysis, test planning, and regulatory compliance. Proficient in SQL querying and data analysis, with experience in enterprise data warehouse environments and automated testing frameworks.
Highest-signal resume keywords
Data Quality ManagementSQL QueryingRoot Cause AnalysisTest PlanningData Governance
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Investigate production data incidents and quality issues
- Perform root cause analysis and identify corrective and preventive actions
- Partner with engineering and operational teams to prioritize remediation activities
- Track recurring issues and recommend long-term quality improvements
- Develop and maintain testing strategies for enterprise data platforms and business-critical processes
- Create test cases, test scenarios, traceability matrices, and validation documentation
- Establish risk-based testing approaches, quality gates, and acceptance criteria
- Collaborate with data engineering teams to develop reusable testing assets and automated validation processes
- Support automated testing for data validation, reconciliation, regression testing, and quality monitoring
- Conduct regression testing across enterprise systems after enhancements, migrations, upgrades, and releases
- Assess downstream impacts, validate production deployments, and determine release readiness
- Support performance, scalability, reliability, recoverability, and operational readiness testing
- Design and execute test plans for complex workflows spanning applications, databases, integrations, and reporting platforms
- Validate data movement across source systems, ETL/ELT processes, data warehouses, reporting environments, and downstream consumers
- Perform integration testing, user acceptance testing support, and production validation
- Partner with stakeholders and product owners to clarify and refine requirements
- Translate business requirements into testable scenarios and validation criteria
- Develop and monitor data quality KPIs, controls, and scorecards
- Support data quality governance initiatives and establish standards, policies, and operating procedures
- Independently validate critical business processes, data assets, reports, dashboards, and regulatory submissions
- Conduct data profiling, reconciliation, root cause analysis, and quality assessments
- Validate business rules, transformations, calculations, aggregations, reporting logic, and data integrity
- Analyze data anomalies, trends, and quality metrics
- Ensure compliance with data governance standards, policies, controls, lineage, retention, privacy, and security requirements
- Support internal and external audits through quality assessments and evidence collection
- Serve as a trusted advisor on data quality and validation practices
- Collaborate across business, technology, risk, compliance, and operational teams
- Mentor junior analysts and promote quality-focused practices
Requirements
What you’ll need- Bachelor's degree in Information Systems, Computer Science, Data Analytics, Business Analytics, or a related field; equivalent work experience considered
- 6+ years of experience in data quality analysis, data warehousing, business systems analysis, data governance, quality assurance, data testing, or business process validation
- Insurance industry experience (P&C and/or Life Insurance)
- Experience supporting enterprise data warehouse environments
- Expertise in data quality management principles and methodologies
- Expertise in end-to-end business process testing
- Expertise in data warehouse validation and reporting verification
- Expertise in data reconciliation and data profiling techniques
- Expertise in SQL querying and data analysis
- Expertise in root cause analysis and problem-solving methodologies
- Expertise in test planning, test design, and test execution
- Expertise in regression testing and release validation
- Expertise in requirements analysis and requirements traceability
- Expertise in data governance and data stewardship practices
- Expertise in regulatory, compliance, and audit-related data validation
- Expertise in production incident investigation and resolution support
- Expertise in data lineage, metadata, and data quality controls
- Expertise in relational database concepts and data modeling
- Expertise in ETL/ELT process and enterprise data pipeline validation
- Advanced SQL development and data analysis
- Experience with Snowflake, Oracle, SQL Server, or similar database platforms
- Familiarity with Informatica, IICS, or enterprise data integration platforms
- Experience with reporting and analytics tools such as Power BI
- Experience with XML, JSON, and API-based integrations
- Familiarity with Python or other scripting languages for data analysis and automation
- Experience with Azure, AWS, or cloud-based data platforms
- Strong analytical and critical thinking skills
- Excellent communication and stakeholder management abilities
- Ability to work independently with minimal supervision
- Strong documentation and organizational skills
- High attention to detail and commitment to data accuracy
- Ability to manage multiple priorities in a fast-paced environment
- Strong intellectual curiosity and continuous improvement mindset
- Preferred: experience with data quality, observability, or governance tools; CI/CD practices and automated testing frameworks; DataOps, DevOps, or Agile delivery methodologies; large-scale cloud data platforms and distributed data ecosystems; AI-assisted testing, validation, and data quality monitoring tools; data lineage, metadata management, and master data management concepts; enterprise audit and regulatory compliance initiatives
Benefits
Comp & perks- Annual discretionary bonus
- Medical benefits
- Dental benefits
- Vision benefits
- Paid time off (PTO)
- 401(k)
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Quality AnalysisData WarehousingData GovernanceData TestingRegression TestingData ReconciliationData ProfilingTest DesignETL/ELT ProcessesData Lineage
Soft Skills
Analytical ThinkingCommunicationStakeholder ManagementAttention to DetailOrganizational Skills
Tools & Technologies
SnowflakeOracleSQL ServerPower BIInformaticaIICSAzureAWSXMLJSON
Industry Keywords
Insurance IndustryP&C InsuranceLife InsuranceRegulatory ComplianceAudit-related Data Validation