Senior Technical Specialist - DBT
Datavail
20h ago
0OtherIndiahimalayas
Data-EngineeringDbt-DevelopmentData-EngineerSnowflakeData-Pipeline-EngineerSenior
Job Description
Title: Snowflake DBT ConsultantLocation: RemoteContract: 3+ MonthsExp Level: 8+ Years Role OverviewWe are looking for a skilled DBT (Data Build Tool) Data Engineer to design, build, and optimize modern data transformation pipelines. The ideal candidate has strong SQL skills, hands-on experience with cloud data warehouses, and a solid understanding of data modeling and ELT best practices. You will work closely with analytics, data science, and business teams to deliver clean, reliable, and well-documented data models.Key ResponsibilitiesData Modeling & DBT DevelopmentDevelop and maintain DBT models (staging, intermediate, mart layers) following modular design and best practices.Implement dbt tests, documentation, sources, macros, and packages.Build reusable and scalable data transformation frameworks.Data Pipeline EngineeringDesign and optimize ELT workflows using DBT integrated with orchestrators (Airflow, Dagster, Prefect, etc.).Work with cloud data environments such as Snowflake, BigQuery, Redshift, Databricks.Ensure high performance of SQL transformations and warehouse queries.Data Quality & GovernanceImplement and maintain data quality tests within DBT (unique, not null, referential integrity).Contribute to version control, CI/CD, documentation standards, and best practices.Collaboration & Stakeholder SupportWork with analysts and business teams to understand requirements and convert them into scalable data models.Support data consumers with well_structured data and documentation (dbt docs).Participate in code reviews and provide engineering guidance.3+ years’ experience in Data Engineering / ELT development.Strong SQL proficiency, with experience writing optimized queries.Hands_on experience with DBT Core or DBT Cloud.Experience with any cloud data warehouse: Snowflake / BigQuery / Redshift / Azure Synapse.Familiarity with Git, CI/CD pipelines, and modern data stack principles.Understanding of data modeling techniques (Kimball, Data Vault, Star/SnowflakeExperience integrating DBT with orchestrators (Airflow, Dagster, Prefect, etc.).Originally posted on Himalayas
