Senior Associate, Data Quality Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and sustain automated data quality checks, validation rules, and exception-handling pipelines utilizing Python.

• Implement and uphold data quality frameworks that align with DAMA-DMBOK and internal governance standards.

• Create and execute data quality metrics, scorecards, and dashboards to monitor completeness, accuracy, consistency, timeliness, and validity across reinsurance datasets.

• Construct and manage data quality monitoring pipelines that integrate with current data infrastructure (e.g., data lake, data warehouse, ETL/ELT workflows).

• Collaborate with data stewards, data owners, and business stakeholders to establish acceptable quality thresholds and remediation workflows.

• Investigate the 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 incorporate quality gates into CI/CD and data pipeline processes.

• Maintain thorough documentation of quality rules, lineage, and remediation outcomes within the data governance catalog.

• Support internal and external audits by supplying data quality evidence and lineage reports.

⛳️ Requirements

• 3–6 years of experience in a data quality, data engineering, or analytics engineering position.

• Experience in reinsurance, insurance, or financial services is preferred.

• Practical experience with SQL and operating in cloud-based data environments.

• Familiarity with cloud platforms such as AWS, Azure, or GCP is preferred.

• Strong proficiency in Python for data processing, quality rule development, and pipeline automation (e.g., pandas, Great Expectations, polars) is preferred.

• Understanding of data governance principles and frameworks (DAMA-DMBOK, DCAM, or equivalent).

• Strong analytical and problem-solving capabilities with meticulous attention to detail.

• Ability to clearly communicate technical data quality concepts to non-technical business stakeholders.

• Knowledge of data controls that support audit, compliance, and reporting requirements is preferred.

🏝️ Benefits

• Annual bonus based on company and individual performance.

• Generous benefits package.