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width="244" height="87"> About Us: Headquartered in New York City with offices throughout the U.S. and in Vancouver, Canada, Hudson is a market-leading specialty insurer that offers a wide range of property and casualty insurance products to corporations, professional firms and individuals through retailers, whole-salers and program administrators. Hudson underwrites specialty primary and excess insurance on an admitted basis through Hud-son Insurance Company and on a non-admitted basis through, Hudson Excess Insurance Company. Hudson Insurance Company is admitted in all U.S. jurisdictions. Hudson has surplus lines eligibility in all U.S. jurisdictions through Hudson Excess Insurance Company. Collectively known as Hudson Insurance Group, its companies are rated A+ (Superior) by A.M. Best, Financial Size Category XV. Hudson Insurance Group is the U.S. Insurance Division of Odys-seyRe, a leading worldwide underwriter of reinsurance and specialty insurance and wholly-owned by Fairfax Financial Holdings Limited. Position Description: Hudson Insurance Group is seeking a Data Modeler to design, develop, and maintain enterprise data models that support our evolving data ecosystem. This role is pivotal in establishing standardized, scalable, and well-governed data structures across our Azure data platform. The ideal candidate will bring a strong understanding of P&C insurance data domains, experience with Erwin Data Modeler, and familiarity with industry data standards such as ACORD. You’ll collaborate closely with data engineers, analysts, and business stakeholders to translate business requirements into logical and physical data models that enable analytics, data integration, and governance initiatives. Applicants must apply directly through our job postings. Direct outreach or solicitation of our hiring managers regarding this position is not permitted. Skills, Knowledge and Abilities: <ul style="margin-bottom:0.0in;margin-top:0.0px"> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Design, develop, and maintain conceptual, logical, and physical data models for enterprise data assets.</li> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Partner with data engineers to ensure models are properly implemented within the Azure Data Platform (e.g., Azure SQL, Synapse, or Data Lake).</li> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Define and manage data standards, naming conventions, and metadata to ensure consistency and reusability across data domains.</li> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Collaborate with business stakeholders to analyze data requirements and ensure alignment with industry models such as ACORD for P&C insurance.</li> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Use Erwin Data Modeler to maintain version control, lineage, and documentation of data models.</li> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Support data governance efforts by maintaining high-quality metadata and complying with organizational data policies.</li> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Review data structures and integration designs to ensure scalability, performance, and data integrity.</li> <li style="margin:0.0in 0.0in 0.0in 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Collaborate with ETL and pipeline developers to align data ingestion and transformation logic with established data models.</li> <li style="margin:0.0in 0.0in 8.0pt 0.0px;line-height:107%;font-size:11.0pt;font-family:Aptos, sans-serif">Participate in peer reviews, design sessions, and model walkthroughs to validate design choices.</li> </ul> Qualifications: Required Qualifications: <ul style="margin-bottom:0.0in;margin-top:0.0px" type="disc"> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Bachelor’s degree in Computer Science, Information Systems, or a related field (or equivalent experience).</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">5+ years of experience in data modeling within a data warehouse or analytics environment.</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Proficiency in Erwin Data Modeler (or similar data modeling tools).</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Strong SQL skills and hands-on experience designing data models for Azure (SQL Database, Synapse, Data Lake, or Databricks).</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">In-depth understanding of data modeling principles (3NF, dimensional modeling, data vault, etc.).</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Experience with P&C insurance data domains, such as policy, claims, billing, and reinsurance.</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Familiarity with ACORD data models and standards.</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Excellent analytical and communication skills with the ability to bridge technical and business perspectives.</li> </ul> Preferred Qualifications: <ul style="margin-bottom:0.0in;margin-top:0.0px" type="disc"> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Experience supporting data governance and metadata management programs.</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Knowledge of data lineage, impact analysis, and data catalog solutions.</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Exposure to Power BI or other reporting/semantic layer tools.</li> <li style="line-height:normal;margin-top:0.0in;margin-right:0.0in;margin-bottom:8.0pt;font-size:11.0pt;font-family:Aptos, sans-serif">Familiarity with data modeling automation or reverse engineering from existing databases.</li> </ul> In New York City, NY the pay range for this role is $110,000-125,000. This role may also be eligible to participate in a discretionary annual incentive program. The specific offer will depend on an applicant’s skills and other factors. This range is specific to New York City, NY and may not be applicable to other locations. We are an E-Verify employer - all hired positions require successfully passing an E-Verify Check. Navigate the links below to learn more about careers at OdysseyRe. <a href="http://odysseyre.com/careers/" target="_blank" rel="noopener">Workplace Initiatives</a> <a href="https://odysseyre.com/careers-u-s/" target="_blank" rel="noopener">Career Areas for Professionals</a> <a href="https://odysseyre.com/rewarding-workplace/" target="_blank" rel="noopener">A Rewarding Workplace</a> Follow us on <a href="https://www.linkedin.com/company/hudson-insurance-group/mycompany/" target="_blank" rel="noopener">LinkedIn</a> for company highlights #Hudson

Data Modeler (New York, NY, US) @ Odyssey Reinsurance Company

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