AI Data Engineer

Start date: ASAP

What you’ll do

• Build and maintain scalable data ingestion pipelines into Snowflake (structured + time-series data)
• Transform raw data into ML-ready datasets (feature engineering, windowed aggregations, lag variables, train/test splits)
• Develop and operationalize ML models in Python (scikit-learn, XGBoost, LightGBM)
• Work within Snowflake using Snowpark to productionize models
• Write model outputs back into Snowflake for AI-driven applications and downstream services
• Ensure production reliability of pipelines and models (monitoring, retraining triggers, data quality checks)

What we’re looking for

• Strong Python skills (data engineering + ML)
• Solid Snowflake experience (SQL, Streams, Tasks, Snowpipe, ingestion patterns, basic performance tuning)
• Hands-on ML experience — you can build, train and deploy models yourself
• Understanding of ML lifecycle in production environments
• Experience with time-series data (window features, irregular series, forecasting) — nice to have
• Familiarity with Azure Data Lake / Azure Fabric — nice to have

Why this role is interesting

• Real AI product impact — not just pipelines, but production ML
• Ownership of end-to-end ML workflows
• Modern stack: Snowflake + Snowpark + Python ML ecosystem
• High autonomy and engineering-driven culture
• Long-term stable project