? Remote – Colombia | ⏳ 6-Month Contract | ? EST Working Hours

Ready to build the data foundation behind cutting-edge AI and Machine Learning solutions?

We're looking for a
Feature Engineer
to help drive Hilton Grand Vacations' ML and AI initiatives by building scalable, reusable data features that power high-impact products. You'll work at the intersection of
Data Engineering, Data Science, and MLOps
, contributing to a centralized
Feature Store in Databricks
and helping bring machine learning models into production.

What You'll Do
- Build and maintain reusable feature pipelines for ML and analytics in Databricks.
- Develop scalable batch and streaming pipelines using
Spark, PySpark, and SQL
.
- Design and enhance a centralized
Feature Store
for reusable business features.
- Create and govern features used across forecasting, personalization, and AI models.
- Ensure consistency between training and inference datasets.
- Support the productionization of ML models, including a key forecasting product.
- Partner with Data Scientists and MLOps teams to deliver reliable,



production-ready features.
- Implement data quality controls, monitoring, lineage, and documentation best practices.

What We're Looking For
- 3–6+ years
of experience in Data Engineering, Analytics Engineering, or Feature Engineering.
- Strong
SQL
and
Python
skills.
- Hands-on experience with
Spark, PySpark, and Databricks
.
- Proven experience building feature pipelines for Machine Learning use cases.
- Direct, hands-on experience building or contributing to a Feature Store (REQUIRED).
- Understanding of ML workflows, including training vs. inference consistency.
- Experience with data quality, monitoring, and large-scale data processing.
- Familiarity with
Azure-based data platforms
.
- Advanced English
.

Why Join?
- Work 100% remotely from Colombia.
- Be part of impactful AI and Machine Learning initiatives.
- Collaborate with cross-functional teams using modern data technologies.
- Contribute t

📌 ML Data Engineer (Colombia)
🏢 Reclutamiento
📍 Colombia