Jobs → Engineering → Senior dbt Engineer

About the Role We are looking for a highly skilled Senior dbt Engineer with strong hands-on experience in dbt (Data Build Tool), SQL, data modeling, and modern cloud data platforms. The ideal candidate will have extensive experience building scalable data transformation pipelines, optimizing complex SQL queries, and implementing data engineering best practices in cloud-based data environments. Key Responsibilities • Design, develop, and maintain scalable data transformation pipelines using dbt Core / dbt Cloud. • Build reusable, modular, and efficient dbt models using SQL, Jinja, and macros. • Develop and optimize complex SQL queries for large-scale data processing. • Implement dimensional data modeling, including Star Schema, Snowflake Schema, and Slowly Changing Dimensions (SCD). • Work with cloud data warehouses such as Snowflake, Databricks, BigQuery, or Amazon Redshift. • Implement data quality checks, automated testing, documentation, and data lineage within dbt. • Optimize dbt model performance, incremental processing, and warehouse resource utilization. • Integrate dbt workflows with orchestration tools such as Airflow, Dagster, or similar platforms. • Implement CI/CD pipelines using GitHub Actions, GitLab CI, or Azure DevOps. • Collaborate with Data Engineers, Data Architects, and Analytics teams to deliver reliable data solutions. • Troubleshoot pipeline failures, data inconsistencies, and performance bottlenecks. Requirements • 8+ years of experience in Data Engineering, Analytics Engineering, or Data Warehousing. • Strong production-level experience developing and managing dbt projects. • Advanced SQL skills including complex joins, CTEs, window functions, query optimization, and performance tuning. • Strong experience with at least one of Snowflake, Databricks, BigQuery, or Redshift. • Expertise in dimensional modeling, Star/Snowflake Schema, SCD Type 1 & 2, and ELT architecture. • Python scripting for data processing, automation, and pipeline development. • Experience with data quality checks, custom validations, data lineage, documentation, and data integrity. • CI/CD & Version Control: Git, GitHub/GitLab, automated testing, and deployment workflows. • Orchestration: Experience integrating dbt with Airflow, Dagster, or equivalent orchestration tools. • Performance Optimization: Hands-on experience optimizing dbt transformations, SQL queries, and large datasets. • Excellent analytical, troubleshooting, and communication skills. • Ability to work independently and collaborate with distributed teams.