Description

You will build and maintain scalable data pipelines and workflows within the Finance and Risk domain.

Responsibilities

• Design and build scalable data pipelines and workflows using Python, PySpark, and Databricks.
• Convert SAS code for analytical assets into Python or PySpark through reverse engineering.
• Analyze business documents and corporate credit risk analytical models to define technical requirements.
• Perform end-to-end testing, debugging, and troubleshooting to ensure implementation meets performance standards.
• Deploy solutions using Azure Pipelines and maintain documentation for migration processes and code changes.

Required Skills

• 5+ years of experience in data engineering.
• Expertise in Python and PySpark.
• Hands-on experience with Databricks.
• Proficiency with Git and CI/CD Azure Pipelines.
• Experience with testing frameworks, debugging tools, and test automation.
• Background in Finance & Risk, specifically with analytical models and modeling.
• Ability to analyze data structures, assess data quality, and resolve inconsistencies.
• Experience converting SAS code to Python/PySpark.
• Any Graduate degree.

Preferred Skills

• Experience building API layers using Python and AppServices to invoke Databricks jobs.

Key Skills

Education

Any Graduate