Role

As a Senior Data Engineer, you will:

Design, develop, test, and maintain scalable data pipelines and data products supporting Enterprise Credit Risk initiatives.
Build and optimize batch and real-time data processing solutions using modern cloud and lakehouse technologies.
Partner with Risk, Product, Data Science, and Engineering teams to understand business requirements and translate them into technical solutions.
Develop reusable frameworks, components, and engineering patterns that improve development efficiency and platform consistency.
Implement data quality controls, monitoring, alerting, and observability capabilities to ensure data reliability and trustworthiness.
Support the migration and modernization of existing data assets and workloads into Databricks and cloud-native platforms.
Build and maintain curated datasets that support lending decisioning, portfolio risk management, and advanced analytics use cases.
Participate in architecture discussions and contribute technical recommendations for platform enhancements.




Troubleshoot production issues and drive root cause analysis to improve platform reliability and performance.
Follow engineering best practices for code quality, testing, deployment automation, security, and operational excellence.
Mentor junior engineers through code reviews, technical guidance, and knowledge sharing.
Continuously evaluate opportunities to improve scalability, performance, cost efficiency, and maintainability of data platforms.

All About You

Essential Skills & Experience

Strong experience developing and maintaining enterprise-scale data engineering solutions.
Hands-on experience with Databricks, Apache Spark, PySpark, Hadoop, SQL, and Python.
Experience building ETL/ELT pipelines and large-scale data processing applications.
Experience working with cloud-based data platforms and storage technologies.
Strong understanding of data modeling concepts and analytical data structures.
Experience implementing automated testi

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