Guidewire Data Analyst

About the Role:
We are seeking a highly skilled and experienced Senior Data Analyst to join our team. The ideal candidate will play a crucial role in interacting with customers, Guidewire Business Analysts (BAs), and the Data Warehouse team to map the Data Warehouse (DW) and Semantic layers. This role requires extensive knowledge of Guidewire Data Dictionaries, data models for PolicyCenter (PC), BillingCenter (BC), and ClaimCenter (CC), as well as proficiency in SQL queries.

Key Responsibilities:
Guidewire Expertise: Utilize vast experience with Guidewire data models (PC, BC, CC) to support data mapping and integration efforts.
Data Warehousing: Collaborate with the Data Warehouse team to review and resolve functional issues.
Customer Interaction: Engage with customers to understand their data needs and provide solutions that align with their requirements.
Business Analysis: Work closely with Guidewire BAs to translate business requirements into technical specifications.
SQL Proficiency: Write SQL queries to provide business transformation logic as needed.
Bridge Role: Act as a bridge between the Data Warehousing team and the Xcenter team, facilitating communication and understanding.
Communication Skills: Possess excellent communication skills to effectively interact with clients, who are transitioning from legacy systems to Xcenters.

Qualifications:
Experience: Extensive experience with Guidewire data models (PC, BC, CC).
Technical Skills: Proficiency in SQL and data mapping techniques.
Communication: Exceptional communication skills to liaise with various stakeholders.
Problem-Solving: Ability to troubleshoot and resolve data-related issues.
Team Collaboration: Proven ability to work collaboratively with cross-functional teams.
Total Experience: Minimum of 10+ years of relevant experience.

Preferred Qualifications:
Experience with Xcenters and understanding of their comparison to legacy systems.
Previous experience in a similar role within the insurance industry.
Basic understanding of Data Warehousing concepts and practices