Snowflake DATA Engineer

Job Title: Data Engineer


Responsibilities:
• Data Pipeline Development: Design, build, and maintain scalable ETL pipelines to ensure efficient data flow from diverse sources into data warehouses.
• Workflow Automation: Utilize Apache Airflow for scheduling and managing complex data workflows.
• Collaboration: Partner with data scientists to implement machine learning models (MLOps) in production.
• Coding and Scripting: Write high-quality Python code for data extraction, transformation, and loading tasks.
• Big Data Processing: Use Databricks for processing large datasets and optimizing data workflows.
• Data Quality Management: Ensure data accuracy and integrity by implementing monitoring, logging, and ing mechanisms.
• Version Control: Use GitHub for code management and collaboration, maintaining clear documentation of data processes.
• Database Management: Work with Snowflake and BigQuery for data storage and analytics, ensuring optimal performance and scalability.
• Performance Optimization: Analyze and tune data storage solutions and SQL queries for efficiency.
• Cross-Functional Support: Collaborate with business units to identify and fulfill data needs effectively.


Basic Qualifications:
• 3+ years of experience in data engineering or a related field.
• Proficient in Python for data processing and scripting.
• Experience with Apache Airflow or similar workflow management tools.
• Familiarity with machine learning operations (MLOps) and model deployment.
• Solid understanding of cloud platforms (AWS, Azure, GCP).
• Strong SQL skills and experience with data modeling.
• Practical experience with Snowflake and BigQuery.


Preferred Skills:
• Knowledge of Databricks for data processing and analytics.
• Experience with data visualization tools like Tableau or Power BI.
• Familiarity with containerization technologies such as Docker.
• Understanding of DataOps principles and practices.