[Top Financial Services] Data Engineer

A prominent financial institution is actively seeking a Data Engineer to join their AI data product team. This role will focus on designing data pipelines, optimizing feature computation, and enabling scalable model deployment with MLOps. It’s ideal for those passionate about combining engineering with real-world AI applications.

What You’ll Do

• Build and optimize feature stores by aggregating external/internal data

• Collaborate with IT teams to collect and process key data for machine learning

• Develop feature engineering pipelines based on business needs

• Design and maintain automated model deployment and retraining systems (MLOps & Auto-Retrain)

• Co-develop data products with ML and business units, and ensure service delivery

What You’ll Bring

• 2+ years of hands-on experience in data engineering or related programming

• Strong coding skills in Python, SQL, and PySpark

• Experience designing and implementing data pipelines

• Familiarity with machine learning workflows and automated deployment

• Logical thinking, communication, and independent problem-solving ability

• Bonus: Project management experience in system integration (for senior candidates)

About the Role

• Highly cross-functional—collaborates with data scientists, IT, and business teams

• Combines model deployment (MLOps) with strong data infrastructure

• Focus on real business impact through intelligent data product development

What’s Next

Excited to engineer smart pipelines and help power financial AI solutions?