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 testing, monitoring, and data quality practices.
- Experience with Data formats ( Parquet, Avro, ORC )
- Knowledge of CI/CD pipelines, Git-based development workflows, and DevOps principles.
- Experience with Workflow orchestration Tools like Airflow
- Strong analytical and problem-solving skills with the ability to work independently on complex technical challenges.
- Effective communication skills with the ability to collaborate across technical and business teams.
- Experience mentoring or supporting less experienced engineers.
- Knowledge of Java Based application development is a huge Plus.
Preferred Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related STEM field or alternative minimum of 5 years of experience in a related field.
Technical Skills
Experience with several of the following technologies:
- Databricks
- Apache Spark / PySpark
- AirFlow
- SQL
- Python
- Delta Lake
- Azure Data Services
- Data Factory or equivalent orchestration tools
- Kafka or streaming platforms
- GitHub
- CI/CD automation
- Data Quality and Observability tools
ADVANCED ENGLISH
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