Systems Analyst Advisor - Commercial Reinsurance

Elevance Health•Richmond, VA

13h•$101,120 - $151,680•Hybrid

About The Position

The System Analyst Advisor is responsible for leading the end-to-end Commercial Reinsurance data and CMS submission process for Elevance Health. This role oversees the analysis, design, implementation, and continuous improvement of the Reinsurance reporting workflow, from identifying eligible claims through final CMS submissions and audit support. The successful candidate will evaluate and redesign existing business processes, develop automated end-to-end solutions, and improve the efficiency, accuracy, and scalability of the Reinsurance program. This role requires working with multiple enterprise data sources—including claims systems, operational databases, and enterprise data warehouses—to ensure complete and accurate data is available for regulatory reporting. As part of Elevance Health's data modernization strategy, this position will also support the migration of legacy SQL and SAS processes to Snowflake and other cloud-based technologies. The ideal candidate is a self-directed, innovative problem solver who takes ownership, drives process improvements, embraces automation, and independently develops technical solutions with minimal direction.

Requirements

Requires an BA/BS degree in Information Technology, Computer Science or related field of study and a minimum of 6 years experience in a variety of technologies, documenting requirements and/or building test cases; or any combination of education and experience, which would provide an equivalent background.

Nice To Haves

Experience supporting Commercial Reinsurance or CMS Reinsurance programs.
Claims processing, claims data analysis, or healthcare claims experience is highly preferred.
Experience identifying claims eligible for CMS regulatory programs.
Experience supporting CMS submissions, CMS inquiries, and federal audits.
Experience with Snowflake and cloud-based data warehouse technologies.
Experience migrating SQL, SAS, or ETL processes to Snowflake, Python, Spark/Snowpark, or similar cloud platforms.
Experience with Microsoft SQL Server.
Experience with enterprise data warehouses, ETL processes, data governance, and data quality best practices.
Experience leading process improvement, workflow redesign, and automation initiatives.

Responsibilities

Lead the end-to-end Commercial Reinsurance data and CMS submission process, ensuring timely, accurate, and compliant submissions.
Evaluate, redesign, and optimize existing Reinsurance workflows to improve efficiency, scalability, automation, and data quality.
Design and implement automated end-to-end processes that reduce manual effort and improve operational performance.
Identify claims eligible for Commercial Reinsurance by analyzing claims, membership, and other enterprise data sources.
Work across multiple data sources, including claims systems, operational applications, enterprise databases, and data warehouses, to support business and regulatory requirements.
Develop, maintain, and optimize complex SQL and SAS programs for data extraction, validation, reconciliation, and regulatory reporting.
Perform deep-dive analysis to investigate data discrepancies, identify root causes, and recommend sustainable solutions.
Support CMS submissions, CMS inquiries, and federal audits through comprehensive data analysis and documentation.
Support User Acceptance Testing (UAT) for enhancements, production releases, and projects impacting Reinsurance submissions.
Analyze business and system changes, assess impacts to the Reinsurance process, and implement effective technical solutions.
Support migration of legacy SQL and SAS processes to Snowflake and other modern cloud-based technologies.
Collaborate with business partners, IT, and external stakeholders while independently leading analytical efforts and recommending technical solutions.
Continuously identify opportunities to automate, modernize, and improve business processes and data workflows.
Document business processes, technical designs, data flows, and operational procedures.