You will build and maintain scalable data pipelines and automation workflows to support data science and business analytics.
Responsibilities
- Design and build scalable ETL pipelines to move data from diverse sources into data warehouses.
- Automate complex data workflows using Apache Airflow for scheduling and management.
- Partner with data scientists to implement machine learning models in production via MLOps.
- Write high-quality Python code for data extraction, transformation, and loading tasks.
- Manage data storage and analytics using Snowflake and BigQuery while optimizing query performance.
Required Skills
- 3+ years of experience in data engineering or a related field.
- Proficiency in Python for data processing and scripting.
- Strong SQL skills and experience with data modeling.
- Experience with Apache Airflow or similar workflow management tools.
- Practical experience with Snowflake and BigQuery.
- Familiarity with MLOps and model deployment.
- Solid understanding of cloud platforms including AWS, Azure, or GCP.
- Experience using GitHub for version control and documentation.
Preferred Skills
- Knowledge of Databricks for data processing and analytics.
- Experience with data visualization tools like Tableau or Power BI.
- Familiarity with containerization technologies.