This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Associate, Data Quality Engineering based in the United States.
This role sits within a specialized Data Governance function focused on ensuring the integrity, reliability, and regulatory readiness of complex insurance and reinsurance datasets. You will help design and implement automated frameworks that validate and monitor data across its full lifecycle, from ingestion through reporting. Working closely with data engineers, actuaries, and business stakeholders, you will embed quality controls into core data pipelines and analytical systems. The role plays a critical part in ensuring that risk, claims, and treaty data meet strict accuracy and compliance standards. You will contribute to building scalable data quality infrastructure in a highly regulated financial environment. This is a hands-on technical position where Python, SQL, and cloud platforms are central to daily work. You will have direct impact on decision-making quality and regulatory confidence across the organization.
Accountabilities:
You will be responsible for building, automating, and maintaining robust data quality frameworks that ensure accuracy, consistency, and compliance across enterprise datasets.
- Design and implement automated data quality checks, validation rules, and exception-handling workflows using Python and SQL.
- Develop and maintain data quality metrics, scorecards, and dashboards covering key dimensions such as completeness, timeliness, and validity.
- Build monitoring pipelines integrated with data lakes, warehouses, and ETL/ELT processes to ensure continuous data integrity.
- Collaborate with data stewards, engineers, and business teams to define data quality thresholds and remediation processes.
- Investigate and resolve root causes of data issues across investment, claims, treaty, and exposure datasets.
- Integrate data quality controls into CI/CD pipelines and broader data engineering workflows.
- Maintain clear documentation of data quality rules, lineage, and audit evidence for governance and compliance needs.
Requirements:
You bring hands-on experience in data quality, data engineering, or analytics engineering within structured and regulated data environments.
- 3–6 years of experience in data quality, data engineering, analytics engineering, or related roles.
- Experience in insurance, reinsurance, or financial services environments is strongly preferred.
- Strong proficiency in Python for data processing and automation (e.g., pandas, data quality frameworks such as Great Expectations).
- Solid SQL skills and experience working with cloud-based platforms such as AWS, Azure, or GCP.
- Familiarity with data governance frameworks such as DAMA-DMBOK, DCAM, or equivalent standards.
- Experience working with large-scale datasets in regulated environments with audit and compliance requirements.
- Strong analytical mindset with exceptional attention to detail and problem-solving ability.
- Ability to communicate complex data quality concepts clearly to both technical and non-technical stakeholders.
- Ownership mindset with the ability to independently drive issues from identification through resolution.
Benefits:
- Base salary range: $120,000 – $130,000 USD, plus annual performance-based bonus
- Comprehensive benefits package including medical, dental, vision, life, and disability insurance
- Eligibility for retirement savings plans (e.g., 401(k))
- Annual bonus tied to individual and company performance
- Opportunity to work on large-scale, mission-critical insurance and reinsurance datasets
- Exposure to advanced data governance and enterprise data architecture practices
- Inclusive and collaborative work culture focused on long-term career development
- Remote-friendly or flexible work arrangements (depending on team structure).