Job Summary

Senior Data Engineer -

• 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.

Key Responsibilities

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.

Skill Requirements

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

Other Requirements