Mortgage Data Engineering & Product Suitability Subject Matter Expert ( SME )
Location : Santa Clara CA , Plano TX , Jersey City NJ, Chicago IL ( Hybrid position)
Data Engineering / Mortgage Technology
Role Overview
We are seeking a highly skilled Senior Mortgage Data Engineering & Product Suitability Subject Matter Expert to lead the design and implementation of advanced mortgage pricing, analytics, and suitability solutions. The ideal candidate will possess deep knowledge of U.S. mortgage products and servicing codes, coupled with hands-on expertise in modern data engineering, streaming architectures, cloud-native development, and ML-based personalization.
This role bridges mortgage domain expertise with technical leadership enabling client bank to leverage data-driven insights for personalized mortgage recommendation for recapture rate uplift among other use cases.
Key Responsibilities
Mortgage Product & Domain Expertise
Understand and interpret a wide range of U.S. mortgage/home loan products (FHA, VA, Conventional, Jumbo, ARM, etc.).
Integrate and normalize data from Loan Origination Systems (e.g., Dark Matter Empower), mortgage servicing systems, AVM property valuation systems, interest rate feeds, and closing cost systems (e.g., Optima Blue).
Support use cases like personalized mortgage suitability for existing borrowers, pricing optimization, and scenario modeling.
Data Engineering & Architecture
Design and implement ELT or zero-ETL pipelines for mortgage portfolio ingestion from systems of record.
Architect Medallion Data Lakehouse pipelines (Bronze/Silver/Gold) with data cleansing, feature engineering, and semantic layers for analytical use cases.
Implement data cataloging for discoverability and governance.
Enable batch, streaming, and CDC-based ingestion using Kafka, Qlik Replicate, Airbyte, and related tools.
Optimize large-scale data storage in Snowflake, AWS RDS/Postgres, or equivalent.
API & Event-Driven Application Development
Build and deploy mortgage product calculators as API services using FastAPI, SQLModel, asyncio, Python.
Implement event-driven architectures with Kafka, AWS SQS/SNS, and asynchronous processing.
Develop API-first Backends-for-Frontends (BFF) architectures to support mortgage product recommendation UIs.
DevOps & DevSecOps
Implement Infrastructure as Code (IaC) using Terraform or Pulumi with AWS.
Manage CI/CD workflows in Git, integrating static and dynamic code analysis(SonarQube, Snyk, etc.).
Embed DevSecOps principles into delivery pipelines.
Proficient in Observability on AWS ( CloudWatch, Grafana )
Frontend Development
Develop responsive, data-driven UI components using React.js, Angular, or similar frameworks.
Integrate frontend applications with backend APIs for real-time mortgage pricing and suitability insights.
Machine Learning & Analytics
Lead ML model development and deployment for mortgage suitability scoring and recommendation.
Leverage AWS SageMaker or equivalent managed ML platforms for model training, inference, and monitoring.
Qualifications
Required:
Bachelor s degree in Computer Science, Data Engineering, or related field; advanced degree preferred.
14-16+ years in data engineering and application development, preferably in the mortgage or financial services sector.
Expertise in U.S. mortgage products, pricing, and servicing data models.
Hands-on experience with Snowflake, Kafka, AWS, FastAPI, and modern data integration tools.
Proficiency in Python, SQL, and modern frontend frameworks.
Proven track record with event-driven architectures and BFF API patterns.
Experience with ML deployment pipelines and cloud-based model hosting.
Preferred:
Experience with Dark Matter Empower LOS, Optimal Blue, AVM integrations.
Familiarity with mortgage regulatory compliance and secondary market guidelines.
AWS Certified Solutions Architect / Data Engineer or equivalent certifications.
Tech Skills:
Key Skill: Fast API, Python, SQL Model
Secondary Skill: Data ingestion knowledge
Good to Have: Front-end/UX development knowledge/experience
Domain Skills:
Mortgage Banking preferred, alternatively good in Banking domain
Soft Skills:
Good consultative mindset, client management skills, offshore team management experience, good communication
Travel/Location:
Hybrid - Can be remote but needs to be able to travel to client site for workshops and engaged meetings.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.