Senior Data Engineer, GFT
Core
Build and maintain scalable data pipelines, feature stores, and MLOps solutions to support AI-enhanced underwriting and ML model lifecycle management in the financial sector.
Role type
Senior Data Engineer (MLOps & Feature Engineering)
Builds
Data pipelines, feature stores, and MLOps infrastructure for AI/ML models
Domain
Financial Services / AI & Machine Learning
Deliverable
production ML models
Required skills
Python, PySpark, Data Engineering/ETL, DevOps/CI-CD, Data Quality & Governance, Feature Engineering, Metadata Management, Cloud Solutions
Preferred skills
Docker, Kubernetes, AWS, Azure, Financial Industry Risk Analytics
Technologies
Python, PySpark, Spark, Pandas, AWS, Azure, Docker, Kubernetes
Responsibilities
Develop feature stores with integrated data quality and governance; Design and implement pipelines for feature extraction, transformation, and storage; Ensure data consistency, lineage, and metadata management; Collaborate with data scientists to standardize feature definitions; Implement reusable pipelines and MLOps solutions; Conduct data analysis, preprocessing, and feature engineering.
Seniority
Senior, hands-on IC
