Note: The job is a remote job and is open to candidates in USA. Gravity Infosolutions, Inc. is seeking a Senior dbt Engineer to build and maintain scalable data transformation pipelines using dbt, SQL, and cloud data platforms. The role focuses on data modeling, pipeline performance, data quality, workflow integration, and collaboration with data and analytics teams.
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
Skills
- Visa Requirement: USC / GC only
- Strong hands-on experience in dbt (Data Build Tool), SQL, data modeling, and modern cloud data platforms
- Dbt: Strong hands-on expertise in dbt Core / dbt Cloud, models, snapshots, seeds, tests, macros, Jinja, and incremental models
- Advanced SQL: Complex joins, CTEs, window functions, query optimization, and performance tuning
- Cloud Data Warehousing: Strong experience with at least one of Snowflake, Databricks, BigQuery, or Redshift
- Data Modeling: Dimensional modeling, Star/Snowflake Schema, SCD Type 1 & 2, and ELT architecture
- Python: Experience with Python scripting for data processing, automation, and pipeline development
- Data Quality: dbt tests, 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
- Strong production-level experience developing and managing dbt projects
- Excellent analytical, troubleshooting, and communication skills
- Ability to work independently and collaborate with distributed teams
- Experience: 7+ Years Preferred
- 8+ years of experience in Data Engineering, Analytics Engineering, or Data Warehousing (preferred)
Company Overview