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.