Job Title: Senior Data Architect / Data Solutions Lead (Insurance)
Location : Hartford, CT 06155 (Hybrid)
Rate : $65/hr.
Salary :$130K
Required Skills as per highlight (Duck creek is good to have not mandate)
· Insurance Expertise : Minimum 5+ years of experience working specifically with Personal Lines data (Automobile, Homeowners, Personal Property).
· Duck Creek Clarity : Deep structural understanding of Duck Creek Clarity schemas, transactional databases, and operational data stores.
· Cloud Data Warehousing : Expert-level design experience with Snowflake, including data sharing, clustering, and cost optimization.
· Relational Databases : Strong mastery of PostgreSQL implementation, indexing, and complex query optimization.
· Programming : Advanced proficiency in Python for data manipulation, scripting, data loading to Duck Creek and ETL frameworks.
· Data Migration Experience : Proven track record of handling large-scale core system migrations with zero data loss.
· Data Quality Tools : Experience with DQ frameworks using custom Python/PostgreSQL-based validations.
Job Overview
We are seeking a Senior Data Architect to design and modernize data platforms across personal insurance lines, specifically Automobile, Personal, and Homeowners insurance . You will lead the modern migration of legacy core systems Mainframe and DB2 into a high-performance Duck Creek cloud ecosystem. Your primary focus will be architecting data solutions using Snowflake, PostgreSQL, and Python, with a specific emphasis on Duck Creek Clarity policy, billing, and claims data models . You will establish robust Data Quality (DQ) frameworks to ensure accurate underwriting analytics, risk profiling, and regulatory reporting.
Domain-Specific Responsibilities
· Multi-Line Integration : Architect data models that unify distinct data streams across Auto (vehicle telematics, driving history) and Homeowners (property risk, geographic data) lines of business.
· Duck Creek Integration : Design and manage ingestion pipelines from Duck Creek Clarity to extract, transform, and load comprehensive policy, billing, and claims workflows.
· Data Migration : Lead complex migration strategies transferring high-volume personal lines historical data from legacy mainframes or relational databases to modern cloud platforms.
· Data Quality Frameworks : Establish automated DQ rules and profiling to ensure pristine financial reporting, accurate loss-ratio calculations, and claims tracking.
· Pipeline Development : Build efficient, reusable data ingestion and transformation pipelines using Python and SQL.
· Predictive Analytics Support : Partner with Actuarial and Underwriting teams to structure data for pricing models, geographic hazard mapping, and customer lifetime value analytics.