Job description

Data Engineer - Data Vault 100% Remote, but tied to Milwaukee, WI 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). Interview process: 1 to 3 rounds conducted via Microsoft Teams. Chance of extension is TBD based on project needs. NON-NEGOTIABLES 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). Candidates unable to work standard US core business hours. Job Description Title: Azure Data Lake / Modeling / Databricks Specialist – Insurance Location: Remote (Milwaukee, WI base) ABOUT THE ROLE 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. KEY 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. REQUIRED QUALIFICATIONS ▸ 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 Job 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. About Us: InterSources Inc , a Certified Diverse Supplier, was founded in 2007 and offers innovative solutions to help clients with Digital Transformations across various domains and industries. Our history spans over 19 years and today we are an Award-Winning Global Software Consultancy solving complex problems with technology. We recognize that our employees and our clients are our strengths as the diverse talents and opportunities they bring to the table enable us to grow as a global platform and they are causally linked with our success. We provide strategic and technical advice, and we have expertise in areas covering Artificial Intelligence, Cloud Migration, Custom Software Development, Data Analytics Infrastructure & Cloud Solutions, Cyber Security Services, etc. We make reasonable accommodations for clients and employees and we do not discriminate based on any protected attribute including race, religion, color, national origin, gender sexual orientation, gender identity, age, or marital status. We also are a Google Cloud partner company. We align strategy with execution and provide secure service solutions by developing and using the latest technologies that thrive our resources to deliver industry-leading capabilities to our clients and customers, making it convenient for our clients to do business with InterSources Inc. Our teams also drive growth by refining technology-driven client experiences that put the users first, providing an unparalleled experience. This results in strengthening the core technologies of clients, enabling them to scale with flexibility, create seamless digital experiences and build lifelong relationships.

Requirements

Must-haves

Data Engineer - Data Vault
100% Remote, but tied to Milwaukee, WI
nternal Notes
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.
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).
Interview process: 1 to 3 rounds conducted via Microsoft Teams.
Chance of extension is TBD based on project needs.
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.
Candidates lacking hands-on Data Vault 2.0 experience (traditional dimensional/star schema only will not suffice).

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.
▸ 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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

azuresqlagilescrum

Platform: jobdiva
Effort: medium