Design, build, and maintain data pipelines supporting mortgage systems, including origination, underwriting, and servicing.
Process large-scale datasets using Apache Spark, with a preference for PySpark.
Develop clean, scalable, and efficient Python code.
Integrate data from multiple sources such as loan systems, credit bureaus, and third-party providers.
Build and optimize ETL/ELT workflows for batch and near real-time processing.
Develop datasets and dashboards using Amazon QuickSight or comparable tools for mortgage reporting and key performance indicators.
Support regulatory and compliance reporting related to loan performance and risk exposure.
Ensure data quality, lineage, and governance across mortgage data platforms.
Collaborate with business stakeholders in risk, underwriting, and operations to translate requirements into data solutions.
Optimize the performance and scalability of data pipelines and storage systems.
