Sr. Associate, Data Quality Engineering

Fortitude Reinsurance Company Ltd. is a leading provider of legacy reinsurance solutions, partnering with top insurance companies. The Data Quality Engineer will be responsible for designing and maintaining automated data quality frameworks, ensuring data accuracy and compliance throughout the data lifecycle.

Responsibilities:

• Design, develop, and maintain automated data quality checks, validation rules, and exception-handling pipelines using Python
• Implement and maintain data quality frameworks aligned with DAMA-DMBOK and internal governance standards
• Develop and implement data quality metrics, scorecards, and dashboards to track completeness, accuracy, consistency, timeliness, and validity across reinsurance datasets
• Build and maintain data quality monitoring pipelines that integrate with existing data infrastructure (e.g., data lake, data warehouse, ETL/ELT workflows)
• Collaborate with data stewards, data owners, and business stakeholders to define acceptable quality thresholds and remediation workflows
• Investigate root causes of data quality issues across investment data, treaty data, claims data, and exposure datasets; document findings and drive resolution
• Partner with data engineering teams to integrate quality gates into CI/CD and data pipeline processes
• Maintain comprehensive documentation of quality rules, lineage, and remediation outcomes within the data governance catalog
• Support internal and external audits by providing data quality evidence and lineage reports

Requirements:

• 3–6 years of experience in a data quality, data engineering, or analytics engineering role
• Hands-on experience with SQL and working in cloud-based data environments
• Strong proficiency in Python for data processing, quality rule development, and pipeline automation (e.g., pandas, Great Expectations, polars)
• Takes ownership of quality outcomes and delivers solutions end-to-end under limited supervision; identifies gaps before they become issues
• Strong analytical and problem-solving skills with a meticulous attention to detail
• Ability to communicate technical data quality concepts clearly to non-technical business stakeholders
• Experience in reinsurance, insurance, or financial services
• Experience with cloud platforms such as AWS, Azure, or GCP
• Familiarity with data governance principles and frameworks (DAMA-DMBOK, DCAM, or equivalent)
• Experience working within structured data environments in financial services, insurance, or reinsurance
• Understanding of data controls supporting audit, compliance, and reporting requirements