Job Description

Data Analyst with AI

We are seeking a detail-oriented and analytical Data Analyst with AI knowledge to join our team. This role will be responsible for collecting, cleaning, analyzing, and interpreting data to support business decision-making.
The ideal candidate must have strong SQL and data visualization skills; should be able to leverage AI to build skills to perform tasks efficiently, a solid understanding of insurance or policy administration data structures, and preferably knowledge of Guidewire and Guidewire Data model.

Key Responsibilities:

• Analyze data from OLTP (transactional) systems and design/build extraction logic to feed OLAP structures such as data warehouses, data marts, and data vaults.
• Write complex SQL queries to extract and analyze data from relational databases and data warehouses.
• Familiarity with the insurance domain — Policy, Claims & Billing.
• Strong technical skillset, with the willingness and ability to take on tasks outside core competency as needed.
• Gather, clean, and validate data from multiple internal and external sources, including core insurance systems.
• Perform data analysis to identify trends, patterns, and insights that guide business strategy and decision-making.
• Collaborate with cross-functional teams to support data-driven projects and initiatives.

Required Qualifications:

• 3+ years of experience in a data analyst or similar analytical role.
• Strong proficiency in SQL and experience working with relational databases.
• Understanding of OLTP vs. OLAP concepts and experience building extraction/transformation logic to populate data warehouses, data marts, or data vault models.
• Strong analytical, problem-solving, and critical-thinking skills.
• Excellent communication skills with the ability to translate technical findings for non-technical audiences.
• High attention to detail and commitment to data accuracy.

Preferred Qualifications:

• Experience working with Guidewire or other P&C insurance systems.
• Exposure to AI agents, including building agents to drive efficient outcomes.