Data Engineer - Python/ETL

Description

Role

• Designing, building, and operating scalable on-premises or cloud data architecture
• Analyzing business requirements and translating them into technical specifications
• Design, develop, and implement data engineering solutions using DBT on cloud platforms (Snowflake, Databricks)
• Design, develop, and maintain scalable data pipelines and ETL processes
• Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.
• Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness
• Implement data governance and security best practices to ensure compliance and data integrity
• Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring
• Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.
  

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Overall 3+ years of prior experience in data engineering, with a focus on designing and building data pipelines
• Experience of working with DBT to implement end-to-end data engineering processes on Snowflake and Databricks
• Comprehensive understanding of the Snowflake and Databricks ecosystem
• Strong programming skills in languages like SQL and Python or PySpark.
• Experience with data modeling, ETL processes, and data warehousing concepts.
• Familiarity with implementing CI/CD processes or other orchestration tools is a plus.