This role offers an exciting opportunity to work on diverse projects, collaborating with cross-functional teams to design, build, and optimize data pipelines and infrastructure.

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 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.