Data Modeler

Job Title

Data Modeler

Job Description Summary

Advisory Intelligence is seeking a midlevel Data Modeler with strong 3NF/relational design expertise who is equally comfortable supporting adjacent data management activities. In addition to building and evolving governed data models, this role contributes to data profiling, data quality reporting, SQL development, and business intelligence dashboard support. We’re looking for a team player who combines handson modeling skills with curiosity and a service mindset, helping the group deliver reliable, consumable data assets that power Advisory products and decisioning.

Job Description

Reports to: Global Director, Data Management & Data Governance (Advisory) 

Location: USbased or overseas; ability and comfort working EST business hours; hybrid/remote options (to be finalized) 


Key Responsibilities 

Enterprise data modeling 

• Design, maintain, and version conceptual/logical/physical models using 3NF normalization; document naming conventions and standards. 
• Apply denormalization patterns selectively for analytics and downstream consumption needs while preserving data quality and lineage. 
• Tooling & metadata management 
• Use ERWin to capture entities, attributes, relationships, indexes, and constraints; enter rich model metadata and steward the model repository. 
• Generate stakeholder review reports and publish model documentation from ERWin; create and review DDL created by ERWin; prepare DML scripts for reference data. 

Data profiling & quality 

• Perform manual and toolassisted data profiling (SQL and/or other available tooling); summarize distributions, anomalies, keys, and referential integrity; feed findings into quality scorecards and remediation actions. 

Integration design & load orchestration 

• Define sourcetotarget mappings (table/columnlevel) including joins, keys, transformations, and data rules; maintain mapping packs for engineering handoff. 
• Determine load sequences for master/reference data across normalized structures; author and review insert/update sequences for batch jobs. 

Analytics & BI support 

• Partner with product and analytics teams to translate modeled data into BIready views; support dashboard teams with semantic layer guidance and consumptionoptimized structures. 

Governance alignment & stakeholder engagement 

• Align models to data governance policies, standards, and business rules; participate in model reviews and change control forums. 
• Facilitate daily communications and meetings; present findings and recommendations clearly to technical and business stakeholders. 

Required Qualifications 

• Demonstrated strength in 3NF normalization and relational modeling techniques; practical experience applying denormalization for analytics/consumption. 
• Hands on experience with ER Win for data modeling, metadata entry, report generation, DDL review, and DML preparation. 
• Proficiency in SQL for profiling and analysis; ability to write performant queries and diagnose data issues via SQL. 
• Ability to author source to target mappings with clear join logic, keys, and transformation rules; meticulous documentation habits. 
• Experience defining insert/update sequences for master/reference data loads across normalized objects. 
• Strong oral and written communication skills; comfortable presenting technical topics to nontechnical stakeholders. 
• Availability to work EST time zone hours and attend daily meetings/communications. 

Nice to Have 

• Familiarity with data governance frameworks and artifacts (data standards, naming conventions, data dictionary) and collaboration with data stewards/architects. 
• Experience supporting business intelligence dashboards and semantic layer design; comfort collaborating with product/analytics teams. 

Competencies 

• Quality & rigor: balances normalized designs with practical consumption needs; insists on clear lineage and documentation. 
• Collaboration: thrives in a federated environment; partners across engineering, analytics, and business. 
• Ownership: proactive about profiling, model hygiene, and production readiness; follows through on action items. 
• Communication: translates modeling decisions into business value; crisp written narratives and visual artifacts. 

Work Environment & Expectations 

This role operates in a professional office environment with standard equipment and collaboration tools. It may require occasional travel for workshops or