Data Analyst
Pubblicato il 13-08-2026 - Association Member Benefits Advisors in Italia
Full-time
Description
AMBA is seeking a talented Data Analyst to join our growing Information Technology Team We are looking for someone with detail oriented skills who thrives in an agile, team-oriented environment.
About AMBA
Since 1981, AMBA has been a trusted provider of essential coverage for retired public servants nationwide. Our reach extends to diverse groups, including hardworking public employees, state retirees, educators, military personnel, trade professionals, firefighters, law enforcement, Unions, Alumni groups, Allied Healthcare, and other non-profit associations. As a full-service marketing and membership development company, we proudly offer outstanding insurance services to our vast network of 44 million members across 450+ associations in all 50 states
Benefits
- Comprehensive benefits package including medical, dental, and vision insurance, spending accounts, and other voluntary benefits.
- Annual Premio Program.
- Corporate 401k Matching.
- Generous time off, 10 paid company holidays, sick time off, and paid parental leave.
- Community Involvement perks, including 1 paid day off each year to volunteer with a local charity of your choice and company volunteer events.
- Support & development to cultivate your knowledge and continuing education to support your professional designations
- Business casual dress code.
- Hybrid work arrangement.
About the Role
Three years ago, AMBA completed the largest acquisition in company history - nearly doubling our size in people and infrastructure almost overnight. Since then, our Data & Analytics team has been quietly doing some of the most consequential work in the company: consolidating two separate, aging reporting environments built around insurance policy administration into a single, trustworthy source of truth.
We've settled on our approach. Data is cleansed and integrated in our on-premises SQL Server environment, then published into Azure Fabric, where we're building semantic models that will p