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.