DBT & Snowflake Engineer

Job description

**Job Description DBT & Snowflake Engineer** **Position** **DBT & Snowflake Engineer / Analytics Engineer** **Role Overview** We are looking for an experienced **DBT & Snowflake Engineer** to design, develop, and maintain scalable data transformation pipelines and analytical data models using **dbt and Snowflake**. The candidate will work closely with Data Engineering, Data Architecture, BI, QA, and Product teams to build high-quality, scalable, and performant data solutions that support enterprise reporting and analytics. **Key Responsibilities** - Develop and maintain **dbt models** on the Snowflake data platform. - Design scalable **staging, intermediate, and data mart models** using dbt. - Develop complex and optimized **SQL queries** in Snowflake. - Implement **incremental models, snapshots, macros, seeds, sources, and dbt tests**. - Design and implement dimensional data models, including **fact and dimension tables**. - Optimize Snowflake queries, warehouses, and data models for **performance and cost efficiency**. - Implement data quality checks, reconciliation, and validation using **dbt tests and Snowflake**. - Establish and maintain **data lineage, documentation, and model dependencies**. - Troubleshoot data discrepancies across source systems, Snowflake, dbt transformations, and reporting datasets. - Work with Data Engineers and Architects to define appropriate **ELT and data transformation strategies**. - Support integration of Snowflake data models with **Power BI and other BI platforms**. - Implement and maintain CI/CD processes for dbt using **Git/GitHub/Azure DevOps**. - Participate in code reviews and ensure adherence to SQL, dbt, Snowflake, and data engineering best practices. - Monitor production transformations and proactively resolve data pipeline and data-quality issues. - Create and maintain technical documentation, data dictionaries, and runbooks. **Mandatory Technical Skills** **DBT** - Strong hands-on experience with **dbt Core or dbt Cloud**. - Experience with dbt models, sources, tests, snapshots, macros, seeds, and incremental processing. - Understanding of dbt project structure, dependencies, exposures, and documentation. - Experience implementing dbt CI/CD and Git-based development workflows. **Snowflake** - Strong hands-on experience with **Snowflake**. - Advanced SQL development and query optimization. - Good understanding of Snowflake architecture and compute/storage separation. - Experience with **virtual warehouses, databases, schemas, stages, views, tables, and secure views**. - Experience with Snowflake performance and cost optimization. - Understanding of Snowflake features such as **Time Travel, Zero-Copy Cloning, Streams/Tasks, and Snowpipe** is preferred. - Experience designing analytical data models within Snowflake. **Data Engineering / SQL** - Strong SQL skills with experience handling complex transformations and large datasets. - Strong understanding of **ETL/ELT architecture**. - Experience with dimensional modeling, star schema, and data marts. - Strong understanding of data quality, validation, reconciliation, and data governance. **Preferred Skills** - Experience with **Power BI** and enterprise BI reporting. - Experience with **Python** for automation or data engineering. - Experience with **GitHub / Azure DevOps and CI/CD pipelines**. - Experience with enterprise-scale **Data Warehouse / Datamart implementations**. - Knowledge of performance tuning and cost optimization in cloud data platforms. - Experience working in Agile/Scrum environments. **Experience** **4–7+ years** of experience in Data Engineering, Analytics Engineering, or Data Warehousing, with strong hands-on experience in **Snowflake and dbt**. **Key Competencies** - Strong analytical and problem-solving skills. - Ability to translate business requirements into scalable data models. - Strong focus on data quality and accuracy. - Good understanding of enterprise data architecture. - Strong communication and collaboration skills. - Ability to work effectively with Data Engineering, BI, QA, Architecture, and Product teams. - Strong ownership and accountability for production data solutions. **Education** Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field. **Mandatory Skills Summary** **Must Have:** - DBT - Snowflake - Advanced SQL - Data Modeling - ETL/ELT - Data Quality & Testing - Git / CI-CD **Good to Have:** - Power BI - Azure Data Lake - Python - SAP - Azure DevOps / GitHub - Data Warehouse / Datamart experience