via Remote Rocketship
$70K - 90K a year
Design and maintain automated data quality checks and pipelines ensuring data accuracy and compliance.
3-6 years in data quality or engineering roles with Python and SQL experience, preferably in financial services and cloud environments.
Job 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
This job posting was last updated on 6/6/2026