Snowflake Data Engineer

Design, develop, and maintain scalable data pipelines using Snowflake. Build and optimize ELT workflows using dbt. Develop and orchestrate data pipelines using Apache Airflow. Design and implement efficient data models to support analytical and business reporting requirements. Perform data ingestion from multiple structured and semi-structured data sources. Optimize Snowflake performance through query tuning, clustering, partitioning, and warehouse optimization. Develop reusable, scalable, and maintainable SQL transformations. Implement data quality checks, validation, and monitoring processes. Collaborate with Data Architects, Business Analysts, BI Developers, and cross-functional teams to deliver robust data solutions. Troubleshoot production issues and ensure high availability of data pipelines. Follow best practices for version control, CI/CD, testing, and documentation. Desired Candidate Profile 8+ years of experience in Data Engineering. Strong hands-on experience with Snowflake. Advanced SQL programming and query optimization. Mandatory experience with Apache Airflow. Mandatory experience with dbt (Data Build Tool). Strong understanding of ETL/ELT concepts and modern data engineering practices. Experience building and maintaining enterprise-scale data pipelines. Proficiency in Python for data engineering and automation. Experience working with Git and version control. Good understanding of data modeling techniques (Star Schema, Snowflake Schema, Dimensional Modeling). Experience working with structured and semi-structured data formats such as JSON, Parquet, and Avro. Strong analytical, debugging, and problem-solving skills. Employment Type Full-time