We are looking for an experienced Data Engineer to join our data team, with strong hands-on expertise in Snowflake and dbt. You'll be responsible for designing, building, and optimizing scalable data pipelines and transformation workflows that power analytics and business decision-making across the organization.
Key Responsibilities Design, build, and maintain robust ELT/ETL pipelines using Snowflake as the core data warehouse Develop, test, and maintain data transformation models using dbt (models, tests, snapshots, macros) Optimize Snowflake performance (warehouse sizing, query tuning, clustering, cost optimization) Implement data quality checks, testing frameworks, and documentation within dbt Collaborate with analytics, BI, and product teams to translate business requirements into reliable data models Manage data ingestion from various sources (APIs, databases, streaming platforms) into Snowflake Contribute to CI/CD practices for data pipeline deployments Ensure data governance, security, and compliance best practices are followed Troubleshoot and resolve data pipeline issues, ensuring high reliability and uptime

Required Qualifications5–6+ years of experience in data engineering roles Strong hands-on experience with Snowflake (data modeling, performance tuning, security/roles, cost management) Proven experience building and maintaining dbt projects (models, tests, macros, documentation) Solid SQL skills and experience with data modeling concepts (star schema, dimensional modeling, etc.) Experience with orchestration tools (e.g., Airflow, Dagster, or similar) Familiarity with version control (Git) and CI/CD pipelines Experience working with cloud platforms (AWS, Azure, or GCP) Strong understanding of data warehousing concepts and ELT/ETL best practices