Description

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python, Snowflake, and SQL
• Build and optimize data warehouse solutions and data models using Snowflake
• Integrate data from multiple sources and implement comprehensive data quality and validation processes
• Optimize Snowflake performance and cloud infrastructure costs across AWS, Azure, or GCP environments
• Troubleshoot production data pipeline issues and ensure data reliability and availability
• Collaborate with analysts, data scientists, and business teams to deliver data-driven solutions
• Follow best practices for code quality, testing, version control, and documentation

Qualifications

• 5+ years of experience in Data Engineering with strong hands-on expertise in Snowflake, SQL, Python, and ETL/ELT
• Advanced SQL skills and strong experience with Python for data processing
• Good understanding of data warehousing concepts and data modeling principles
• Experience with cloud platforms (AWS, Azure, or GCP) and data pipeline orchestration tools
• Experience with Git and CI/CD practices for version control and deployment
• Strong problem-solving abilities and excellent communication skills
• Experience with Airflow, dbt, Azure Data Factory, or AWS Glue preferred
• Knowledge of Spark/PySpark and Snowflake advanced features (Streams, Tasks, Snowpipe, Dynamic Tables, Snowpark) is a plus
• Exposure to Kafka, data governance, and data security best practices

Key Skills

Education

Any Gradute