> Markdown version of [/jobs/ext/2055857-lead-data-modeler](https://www.wearedevelopers.com/jobs/ext/2055857-lead-data-modeler). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Lead Data Modeler

- **Company:** Kaizen Technologies Inc
- **Location:** Charlotte, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Big Data, BigQuery, Cloud Computing, Cloud Engineering, Cloud Storage, Information Systems, Data Discovery, Data Structures, Data Flow Control, Meta-Data Management, Metadata Standards, PowerDesigner, Cloud Services, Cloudera, SAP (Applications), SQL Databases, Google Cloud, Information Technology, Google Bigquery, Physical Data Models, Cloud Migration, Legacy Systems
- **Published:** August 14, 2026
- **Apply:** https://www.dice.com/job-detail/80686e80-8684-46be-be90-fc8710da76ba

## About the Role

* Bachelor's Degree in Computer Science, Information Systems, Engineering, Finance, or related discipline.
 * 12+ years of Data Modeling experience.
 * 5+ years within Banking, Financial Services, or Regulatory Reporting.
 * Experience supporting large-scale Data Warehouse or Cloud Modernization initiatives.
 * experience in Home Lending and Mortgage data domains.
 * supporting FR Y-14 regulatory reporting initiatives or similar regulatory exposure
 * Experience working with Large U.S. Banks.
 * Familiarity with risk and finance data domains.
 * Experience working in Agile delivery environments.
 * Knowledge of AI-assisted data discovery and metadata management tools.

## Description

The Data Modeler will be responsible for developing conceptual, logical, and physical data models for Home Lending and FR Y-14M reporting domains. The individual will collaborate closely with business stakeholders, regulatory reporting teams, data architects, data engineers, business analysts, governance teams, and cloud engineering teams to establish standardized and scalable data structures within the Google Cloud Platform ecosystem. This role requires a deep understanding of mortgage data, loan lifecycle processes, regulatory reporting data requirements, and cloud-native data architecture patterns., * Data Modeling & Architecture

 * Design and maintain conceptual, logical, and physical data models for Home Lending and Regulatory Reporting domains.
 * Develop scalable data models optimized for Google BigQuery.
 * Create enterprise data structures supporting below or similar:
 + Mortgage Origination
 + Mortgage Servicing
 + Customer Information
 + Collateral Data
 + Loan Performance
 + Delinquency Management
 + Loss Mitigation
 + Regulatory Reporting
 * Define data relationships, cardinality, business rules, and metadata standards.
 * Design canonical and harmonized data models across multiple source systems., Data Modeling Tools
 * ERwin Data Modeler
 * ER/Studio
 * SAP PowerDesigner
 * SQL Developer Data Modeler

Cloud & Engineering

 * Google Cloud Platform BigQuery
 * Dataflow
 * Dataproc
 * Cloud Composer
 * Cloud Storage, * Deliver enterprise-grade data models supporting Home Lending and FR Y-14M reporting.
 * Enable migration from legacy platforms to Google Cloud Platform BigQuery.
 * Improve data consistency, quality, and regulatory compliance.
 * Establish scalable and reusable regulatory reporting datasets.
 * Support reduction of reporting complexity and improved data traceability.
 * Enable self-service analytics and future-state regulatory reporting capabilities.


## Related Videos

- [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail)
- [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works)
- [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology)
- [Data Fabric in Action - How to enhance a Stock Trading App with ML and Data Virtualization](https://www.wearedevelopers.com/videos/253-data-fabric-in-action-how-to-enhance-a-stock-trading-app-with-ml-and-data-virtualization)
- [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai)
- [Making Data Warehouses fast. A developer's story.](https://www.wearedevelopers.com/videos/302-making-data-warehouses-fast-a-developer-s-story)

## Related Articles

- [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)
- [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)
- [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)
- [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)
- [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)