Data Warehouse Developer

Cornerstone Capital Bank•Englewood, CO

2d•Onsite

About The Position

Design, build, and optimize database objects and data pipelines within a Snowflake platform supporting mortgage loan servicing operations. Develop and maintain dbt transformations that move data through a medallion architecture (Raw → Staging → Quarantine → Production → Analytics), build API-serving data layers, and ensure performant, reliable data delivery across a large-scale environment (100B+ rows, 10,000+ tables).

Requirements

Bachelor's degree in Computer Science, Information Systems, or related field — or equivalent professional experience.
3+ years developing in Snowflake (DDL, DML, stored procedures, tasks, streams, UDFs).
Strong dbt experience (models, tests, incremental strategies, macros, packages)
Advanced SQL: window functions, CTEs, semi-structured data (VARIANT/JSON), query optimization
Experience with Azure Data Factory for orchestration and data movement
Experience with Azure Function Apps for event-driven and API-based data integrations
Familiarity with RESTful API design, development, and consumption (JSON payloads, authentication, error handling)
Understanding of medallion/layered data architecture patterns
Understanding of mortgage servicing data: loan-level records, payment transactions, escrow, collections, delinquency, credit reporting
Experience with Snowflake features: multi-cluster warehouses, external stages, storage integrations, notification integrations (Event Grid, Storage Queue)
Python for Azure Functions, data processing, and pipeline automation
Experience with Snowflake external functions and API integrations
Knowledge of OAuth, API key management, and secure service-to-service communication
Knowledge of GSE reporting structures (Fannie Mae, Freddie Mac)
Git-based workflow for database development; CI/CD with dbt Cloud
Snowflake RBAC administration and role-based access patterns

Responsibilities

Develop and maintain dbt models powering production and analytics layers
Build and optimize SQL objects: tables, views, stored procedures, tasks, and streams
Design and implement data ingestion patterns from Azure storage via ADF pipelines and Snowpipe
Develop data quality and quarantine logic to validate and gate data before promotion to production
Build and maintain API-serving schemas delivering data to operational systems
Develop and support Azure Function Apps that interact with Snowflake for real-time and event-driven data operations
Implement loan boarding and MERS registration data pipelines
Optimize query performance across multicluster warehouses; tune clustering keys, materialized views, and partition strategies
Develop audit trails and historical tracking patterns
Support extract pipelines delivering data to investors, regulators, and partners via Azure storage
Manage schema migrations, version control via GitHub, and CI/CD through dbt Cloud
Track and report Success Metrics
Evaluate pipeline reliability and on-time data availability
Evaluate query performance improvements and warehouse credit efficiency
Evaluate API response time and availability SLAs
Evaluate Data quality pass-through accuracy
Perform Code quality: test coverage, documentation, PR review turnaround