
Chief Data Quality Specialist
2 days ago
Lead data quality initiatives in insurance data ecosystems.
Key Responsibilities:- Quality Assurance: Develop comprehensive testing strategies to ensure data analytics product reliability.
- Data Analysis: Validate data integrity, accuracy, and insights generated by analytics processes.
- Collaboration: Work with developers and stakeholders to streamline testing efforts and improve product quality.
- Requirements and Documentation: Clearly communicate complex tasks and ensure thorough documentation.
- Automation: Implement automation strategies for data processes and maintain system efficiency.
Develop and execute comprehensive data validation and quality assurance plans for insurance data pipelines. Perform data quality audits, identify anomalies, and lead root cause analysis efforts. Design and implement automated data quality checks. Validate data feeds and transformations related to regulatory reporting and risk management frameworks. Collaborate with cross-functional teams to define data quality metrics, business rules, and SLA thresholds. Document test plans, QA findings, and remediation actions according to compliance and audit standards. Provide QA oversight on data projects involving underwriting systems, policy administration platforms, and claims processing workflows. Mentor junior QA analysts and advocate for best practices in data governance and quality control.
Required Qualifications:- Bachelor's degree in Data Science, Computer Science, Information Systems, or a related field. Master's degree is a plus.
- 8+ years of experience in data QA, analytics, or engineering—ideally in the insurance industry.
- Advanced SQL skills with experience working on large-scale, complex data sets.
- Hands-on experience with data quality frameworks, test automation tools, and scripting languages.
- Understanding of insurance operations, data workflows, and compliance requirements.
- Actively communicate quality issues related to data collection, storage, processing, or usage.
- Investigate, troubleshoot, and document data issues from internal and external customers.
Strong analytical, documentation, and communication skills.
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