About the Role :

We are looking for an experienced Data Engineer with strong expertise in Snowflake, dbt, SQL, and Python/PySpark to design, develop, and optimize scalable data pipelines and cloud-based data warehouse solutions.

Responsibilities :

- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.

- Build and manage data transformation models using Snowflake and dbt.

- Write complex SQL queries and optimize query performance and warehouse utilization.

- Develop data processing solutions using Python and/or PySpark.

- Design and optimize data models to support analytics and business requirements.

- Integrate data from multiple sources while ensuring data quality, consistency, and reliability.

- Leverage AWS or Azure services to build and maintain cloud-based data solutions.

- Monitor pipeline performance, troubleshoot failures, and resolve data processing issues.

- Collaborate with business, analytics, and engineering teams to deliver reliable data solutions.

- Follow best practices for code quality, data security, performance, and maintainability.

Requirements :

- 6 - 10 years of experience in data engineering or a related field.

- Strong hands-on experience with Snowflake and SQL.

- Experience with dbt for data transformation and model development.

- Proficiency in Python and/or PySpark.

- Strong understanding of data warehousing, data modeling, and ETL/ELT processes.

- Experience with AWS or Azure cloud services for data engineering.

- Proven experience developing, maintaining, and optimizing scalable data pipelines.

- Strong analytical, troubleshooting, and problem-solving skills.