Role : Data Analyst_EDM
Location: West Des Moines, IA
FTE ONLY
Must Have Technical/Functional Skills
We are looking for a Data Analyst with strong experience in Insurance, Risk, and Data Engineering concepts to support data analysis, reporting, and solution delivery for insurance clients. The role involves working with policy, claims, underwriting, and risk-related data, while also leveraging cloud platforms, data warehouse environments, and data modeling practices to build insights and support software product development, client projects, and business decisions.
Key Responsibilities
• Analyze insurance data such as policies, claims, premiums, underwriting data, and customer records
• Support risk analytics, including identifying trends, anomalies, and potential risk indicators
• Work with cross-functional teams (BA, QA, Developers, Product Owners) to understand business requirements
• Prepare dashboards, reports, and visualizations using BI tools
• Perform data cleaning, validation, and quality checks
• Support data mapping, data migration, and API/DB validation activities
• Assist in documenting data definitions, rules, and business logic
• Communicate insights and findings to technical and business teams
• Work with Data Warehouses (DWH) for data extraction, transformation, loading (ETL/ELT)
• Utilize AWS cloud services for analytics, storage, and data processing (e.g., S3, Redshift, Athena, Glue)
• Create and maintain data models (conceptual, logical, and physical) to support reporting and analytics
Required Skills
• Strong proficiency in SQL and Excel.
• Experience with BI tools like Power BI, Tableau, or Qlik.
• Basic knowledge of Insurance workflows (Policy, Claims, Underwriting).
• Understanding of risk concepts such as exposure, trends, and early warning indicators.
• Ability to interpret data patterns and convert them into meaningful insights.
• Hands-on experience working with Data Warehouse concepts (star schema, fact/dimension tables).
• Knowledge of AWS services related to data analytics.
• Experience in data modeling and understanding of normalization/denormalization techniques.