ESIS AVP, Claims Data Integration & Migration

ESIS is seeking an AVP of Claims Data Integration & Migration to lead the intake, conversion, and integration of claims data from external sources into enterprise systems. This position is essential for delivering accurate, scalable client onboarding and directly contributes to operational performance and client satisfaction.

This is a hybrid position, with three days per week in the Philadelphia office.

Key Responsibilities

• Lead and support a team of three analysts, establishing priorities and promoting high-quality outcomes.
• Oversee the end-to-end delivery of multiple, concurrent data conversion and client onboarding projects.
• Manage the mapping, validation, and integration of claims data from diverse external sources and formats into enterprise systems.
• Serve as the primary liaison for stakeholders, facilitating effective communication, risk management, and adherence to project timelines.
• Identify and implement process improvements to enhance scalability, efficiency, and data quality.
• Collaborate with technical teams to translate business requirements into practical, effective solutions.
• Provide hands-on support for complex data analysis, troubleshooting, and solution design, ensuring timely resolution of issues to meet client needs.
• Act as a subject matter expert on claims data and workflows, guiding technical projects from concept through successful implementation.

• 5–8 years of experience in data analysis, systems analysis, data migration, or related roles, preferably within insurance, claims, healthcare, or RMIS environments
• Experience with data integration, conversion, onboarding, or system implementation projects
• Strong background in business process analysis and workflow optimization to improve performance and scalability
• Experience leading complex, high-visibility initiatives in cross-functional environments
• Ability to manage multiple priorities and deliver results in fast-paced environments
• Strong analytical, critical thinking, and problem-solving skills, including experience working with large and complex data sets
• Proficiency in data mapping and working with multiple data sources and formats
• Ability to understand complex enterprise systems and technical processes
• Experience collaborating with technical teams and external partners
• Strong interpersonal, written, and verbal communication skills, with the ability to communicate effectively with both technical and business stakeholders
• Highly organized, detail-oriented, and committed to delivering quality outcomes
• Ability to build collaborative relationships and coordinate work across teams under tight timelines
• Bachelor’s degree or equivalent professional experience

Preferred Qualifications

• Familiarity with SQL, including the ability to write or modify select queries to support data integration efforts
• Experience improving processes and supporting operational scalability
• Experience with insurance, claims, or RMIS systems

Sponsorship, now or in the future, is not available for this role. Applicants must be legally authorized for employment in the U.S. without need for current or future employment-based sponsorship.

ESIS, a Chubb company, provides claim and risk management services to a wide variety of commercial clients. ESIS’ innovative best-in-class approach to program design, integration, and achievement of results aligns with the needs and expectations of our clients’ unique risk management needs. With more than 70 years of experience, and offerings in both the U.S. and globally, ESIS provides one of the industry’s broadest selections of risk management solutions covering both pre- and post-loss services.

The pay range for the role is $139,700 to $161,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.