Responsibilities:

· 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 4+ 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.