Data Engineer - Data Vault

The company is seeking a highly skilled Insurance P&C Data Analyst and Data Modeler to support a critical data engineering and enterprise data platform transformation project. The role focuses on designing Atomic Data Vault models, performing source-to-target mapping, analyzing insurance data, and supporting ingestion, data quality, BI, and analytics initiatives.

Responsibilities:

• Design and implement Atomic Data Vault (ADV) models including Hub, Satellite, and Link table structures from source system analysis
• Perform end-to-end Source-to-Target Mapping (STM) for insurance data domains including policy, claims, billing, and reinsurance
• Use Erwin Data Modeler to design, document, and maintain logical and physical data models across enterprise data warehouse and data vault layers
• Collaborate with business stakeholders to gather P&C insurance data requirements and translate them into robust data models
• Analyze source system tables and columns to identify and classify Hub, Satellite, and Link candidates for Data Vault architecture
• Develop and maintain data lineage documentation, data dictionaries, and metadata artifacts
• Partner with engineers and architects on ingestion pipelines, ETL/ELT processes, and data quality frameworks
• Conduct data profiling, anomaly detection, and root-cause analysis across P&C insurance datasets
• Support BI and analytics teams with data models that enable self-service reporting across claims, underwriting, and premium analytics

Requirements:

• ▸ Experience: 6–10 years of progressive experience in data analysis and data modeling roles
• ▸ Insurance Domain: Demonstrated hands-on experience in Property & Casualty insurance data domains (policy, claims, billing, agents, reinsurance)
• ▸ Data Vault: Strong proficiency in Atomic Data Vault (ADV) modeling principles — Hubs, Links, Satellites, Reference tables, and Point-in-Time constructs
• ▸ STM: Proven ability to perform Source-to-Target Mapping for complex, multi-source insurance environments
• ▸ Erwin: Expert-level use of Erwin Data Modeler for logical, physical, and dimensional modeling
• ▸ DV Classification: Strong ability to review raw source tables/columns and identify the correct Data Vault entity type (Hub, Link, or Satellite) with clear business key and relationship rationale
• ▸ Analytical: Excellent analytical skills with the ability to interrogate data, identify patterns, and draw business insights
• ▸ SQL: Strong SQL proficiency across major platforms (SQL Server, Oracle, Snowflake, or similar)
• ▸ Insurance data domain expertise (P&C lines of business)
• ▸ Atomic Data Vault design and implementation
• ▸ Source-to-Target Mapping discipline and documentation
• ▸ Hub / Satellite / Link identification and classification
• ▸ Erwin Data Modeler proficiency
• ▸ Data profiling and analytical problem-solving
• ▸ Cross-functional stakeholder communication
• • ▸ Attention to detail and data quality mindset
• ▸ Experience with cloud data platforms on Azure Synapse
• ▸ Familiarity with Data Vault 2.0 standards and automation tooling
• ▸ Experience working in Agile/Scrum delivery environments
• ▸ Exposure to BI tools such as Power BI