We are seeking an experienced Machine Learning Engineer to build and manage our data infrastructure. This role will focus on designing ETL pipelines, implementing a Snowflake data warehouse, and developing machine learning solutions that drive business value.

• Design, develop, and maintain scalable ETL pipelines to process data from multiple sources
• Build and optimize our Snowflake data warehouse architecture
• Implement real-time data streaming solutions using Kafka
• Develop and deploy machine learning models to production
• Ensure data quality, security, and compliance across all systems
• Collaborate with the Data Science team to implement ML solutions
• Document data architecture, pipelines, and processes

• 3+ years of experience in data engineering or machine learning engineering
• Strong programming skills in Python
• Expertise with Snowflake or similar cloud data warehouses
• Experience with ETL/ELT processes and tools (Airflow, dbt, etc.)
• Hands-on experience with Kafka for real-time data streaming
• Knowledge of SQL and NoSQL databases
• Experience with cloud platforms (AWS)
• Understanding of data modeling, data architecture, and data governance

• Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Knowledge of container technologies (Docker, Kubernetes)
• Experience with CI/CD pipelines
• Familiarity with data visualization tools
• Strong understanding of software engineering best practices

• Cloud Data Warehouse: Snowflake
• Data Streaming: Apache Kafka
• Programming: Python, SQL
• Orchestration: Apache Airflow
• Version Control: Git
• ML Frameworks: TensorFlow, PyTorch, scikit-learn
• Data Transformation: dbt
• Cloud Platforms: AWS