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.
- Experie

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