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# Remote Sr Data Engineer

- **Company:** SR Talent Solution Inc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Airflow, Amazon Web Services, Microsoft Azure, Big Data, Continuous Integration, Data Validation, Extract Transform Load (ETL), Data Security, Data Warehousing, Dimensional Modeling, Python (Programming Language), Performance Tuning, SQL Databases, Google Cloud, Sql Optimization, Snowflake, Apache Spark, Git, Apache Kafka, Data Pipelines, Databricks
- **Published:** September 25, 2026
- **Apply:** https://www.dice.com/job-detail/eed52971-5845-4eb7-b0d3-92e15ed40764

## About the Role

Title: Remote Sr Data Engineer-15+ years
Duration: 6 months/contract
Must have 3+ years of U.S. mortgage or lending-domain exp, * 15+ years of data-engineering experience.

 * Strong hands-on Snowflake and advanced SQL expertise.
 * 3+ years of U.S. mortgage or lending-domain experience.
 * Experience with ETL/ELT, data warehousing, dimensional modeling, and large datasets.
 * Understanding of mortgage origination, underwriting, closing, servicing, payments, escrow, and loan lifecycle.
 * Experience with Python, Git, and AWS, Azure, or Google Cloud Platform.

Preferred

Experience with dbt, Airflow, Spark, Databricks, Kafka, CI/CD, and Snowflake Streams, Tasks, Snowpipe, or Dynamic Tables. Familiarity with MISMO, Fannie Mae, Freddie Mac, FHA, and VA mortgage data is highly desirable.

Client is seeking a Senior Data Engineer with strong Snowflake expertise and hands-on experience working with U.S. mortgage data. The consultant will design and maintain scalable data pipelines supporting mortgage operations, reporting, and analytics.

## Description

* Develop scalable ETL/ELT pipelines using Snowflake and SQL.
 * Integrate loan-origination, underwriting, servicing, borrower, payment, property, and third-party data.
 * Build data models and curated datasets for analytics and reporting.
 * Perform data validation, reconciliation, cleansing, and performance optimization.
 * Troubleshoot production pipelines and enforce data security and governance.
 * Collaborate with business, architecture, QA, and application teams.


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