Machine Learning Engineer / Data Scientist (Databricks & Snowflake)

ML Engineering & MLOps

• Productionize ML models using MLflow for experiment tracking, model registry, and lifecycle management
• Implement CI/CD pipelines for ML workflows
• Monitor model performance and manage version control
• Ensure reproducibility and governance of ML assets
• Manage feature pipelines and model retraining strategies

Databricks & Distributed Processing

• Build scalable data pipelines using Databricks (Spark)
• Optimize distributed workloads for performance and cost efficiency
• Implement notebook-based and production-grade job workflows
• Leverage Unity Catalog for governance, lineage, and secure data/model access control

Data Warehousing & Snowflake

• Design and optimize data models in Snowflake
• Write advanced SQL queries for transformation and analytics
• Integrate Snowflake with Databricks for seamless data workflows
• Support ELT/ETL design and performance tuning