Data Engineer - Feature Engineering, Semi Senior (Remote - Latam)

A remote-first data products and machine learning company is hiring a semi-senior data engineer to build the features used by a credit risk scoring model for a large multinational client. The work focuses on turning transactional and credit behavior data into reliable, reusable and well-documented signals. The role sits between the modeling and platform teams and emphasizes governance, auditability and consistency between training and production.

What you'll do

• Design features from transactional and credit behavior data, such as frequency, recency, monetary amounts, digital engagement and delinquency indicators, for a credit risk model.
• Implement features with complete metadata, including descriptions, keys, lineage, ownership, tags, lifecycle and temporal logic, and design them for reuse across projects.
• Follow the team's deployment pipeline, from bundle validation through table creation to production, and monitor jobs with attention to cost efficiency.
• Keep training and production feature definitions consistent so the model has a single source of truth.

What you need

• Hands-on experience in feature engineering or data engineering on Databricks with Unity Catalog.
• Advanced SQL and Python skills.
• Working knowledge of data governance, lineage and data quality practices, including tools such as DQX.
• Familiarity with naming conventions and metadata standards.
• Must be based in Latin America to be eligible for this role.
• Nice to have: Feature Store certification and experience with financial data or AI agent frameworks.

Applicants must be based in: Brazil, Mexico, Colombia, Argentina, Chile, Peru.

How to apply

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