Senior Associate, Data Quality Engineering

🕒 June 1

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Logo of Fortitude Re

Fortitude Re

201 - 500 employees

💸 Finance

⚕️ Healthcare Insurance

Finance • Healthcare Insurance

Fortitude Re is a reinsurance company that specializes in helping insurance companies around the world address their complex risk transfer challenges. The firm designs and delivers customized solutions for legacy Life & Annuity and Property & Casualty (P&C) insurance lines. Backed by experienced investor groups including The Carlyle Group and T&D Insurance Group, Fortitude Re prides itself on its leadership with over 20 years of industry experience to effectively manage legacy liabilities. Fortitude Reinsurance Company Ltd. , along with its subsidiaries, operates globally with a significant presence in Hamilton, Bermuda.

📋 Description

• 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 • Experience in reinsurance, insurance, or financial services preferred • Hands-on experience with SQL and working in cloud-based data environments • Experience with cloud platforms such as AWS, Azure, or GCP preferred • Strong proficiency in Python for data processing, quality rule development, and pipeline automation (e.g., pandas, Great Expectations, polars) preferred • Familiarity with data governance principles and frameworks (DAMA-DMBOK, DCAM, or equivalent) • 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 • Understanding of data controls supporting audit, compliance, and reporting requirements preferred

🏖️ Benefits

• Annual bonus based on company and individual performance • Generous benefits package

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