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.
Key Responsibilities
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
Required Skills & Experience
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
Preferred Qualifications
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