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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - Data Vault - **Company:** Intersources Inc. - **Location:** Milwaukee, WI, United States (Remote available) - **Experience:** Expert - **Contract:** Temporary contract - **Skills:** Data Analysis, Profiling, Data Architecture, Data Dictionary, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Mapping, Data Migration, Data Profiling, Data Structures, Data Vault Modeling, Data Warehousing, Dimensional Modeling, Systems Analysis, Meta-Data Management, Microsoft SQL Server, Oracle (Applications), Power BI, Cloud Services, Standard Sql, Azure Data Lake, SQL Databases, Data Processing, Data Ingestion, Beeline, Snowflake, Pure Data, Star Schema, Azure Synapse Analytics, Databricks - **Published:** September 10, 2026 - **Apply:** https://www2.jobdiva.com/portal/?a=62jdnw10t7d77ytz0lbaey9qxonk3b05a9tqw96rb7z6hlfo7xj79l9g6mp6aj2o&compid=0/jobs/32977793#/jobs/32977793 ## About the Role Education: No specific degree explicitly required by client. Data Vault 2.0 Modeling (5+ years) - Expert-level hands-on capability in designing Hubs, Links, and Satellites. Insurance Domain Expertise (3+ years) - Practical working knowledge of insurance data structures (claims, policies, underwriting, financial data). Data Processing & Migration (5+ years) - End-to-end execution of schema mapping, profiling, cutover planning, and Medallion architecture execution. NICE-TO-HAVES Azure Data Lake and Databricks pipeline build experience. Data quality assessment and automated reconciliation rule definition. Metadata management, lineage mapping, and business glossary creation. DISQUALIFIERS Candidates lacking hands-on Data Vault 2.0 experience (traditional dimensional/star schema only will not suffice). Candidates with zero domain experience in Insurance systems (policies/claims/financials)., * 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). PREFERRED QUALIFICATIONS * 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 CORE COMPETENCIES * 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 ## Description nternal Notes Feedback on candidates: we are not looking for pure data engineering profiles for this role, we need someone who has Insurance functional experience, atomic data vault modeling & mapping experience. This is going to be tough combination. MUST HAVE -: insurance / ADV experience Met with Sandeep for intake on 196767-1. He was not aware of the BOT program so shared with him more about that. the role in beeline doesn't have what he's looking for because he doesn't want to work through Beeline, wants candidates directly. He's sending me the JD. Looking for a Data Modeler/Business Analyst. Most important is Incident experience! Must have Atomic Data Vault experience. Also source to target mapping experience. This will be a short contract to start (2-3 months) but he needs probably 10 resources so if this goes well, he'll hire more people and will extend this persons contract because they also have a lot of projects coming up. Process: 2 interviews (one short 10-15 minutes with Sandeep, one longer tech interview with SME) Work setup: 100% Remote, but tied to Milwaukee, WI location (no local requirement). Core hours standard US time zones. Reason for opening: Critical enterprise data platform transformation project requiring specialized Data Vault 2.0 and insurance domain knowledge. Deliverables: End-to-end data migration, Medallion architecture (Bronze/Silver/Gold) ingestion/transformation pipelines, source-to-target mappings, and Data Vault modeling (Hubs/Links/Satellites)., We are seeking a highly skilled Insurance P&C Data Analyst & Data Modeler to join our data engineering team. The ideal candidate brings deep Property & Casualty insurance domain knowledge combined with expert-level data modeling capabilities, particularly in Atomic Data Vault methodology. You will play a critical role in designing and implementing scalable, auditable data architectures that power analytics across our insurance lines of business., * 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.