[Remote] Data Engineer - Data Vault
Note: The job is a remote job and is open to candidates in USA. 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
Skills
- ▸ 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
Benefits
- 100% Remote, but tied to Milwaukee, WI
- Core hours standard US time zones
Company Overview
Company H1B Sponsorship