Lead Data Engineer (Snowflake, DBT and Qlik)-7
Role summary
The Lead Data Engineer will be responsible for designing, developing, and maintaining scalable data transformation pipelines using dbt on the Snowflake platform. This role requires expert-level proficiency in SQL, Snowflake, and dbt, including advanced modeling techniques and performance optimization. The Lead Data Engineer will collaborate with stakeholders to translate data requirements into effective data models, ensure data quality and integrity, and implement data governance policies. Experience with version control (Git) and data warehousing concepts is essential. The position is full-time and onsite.
Phoenix, Arizona 85001 Posted March 29th, 2026
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Job Type: Full Time
Job Category: IT
Job Description
Role - Lead Data Engineer (Snowflake, DBT and Qlik)
Location - Raleigh, NC | Phoenix, AZ | Dallas, TX (ONSITE)
Experience - 10+
## Type - Full Time
Job Description
Design, develop, and maintain robust and scalable data transformation pipelines using dbt on the Snowflake platform.
DBT Macro Development to Create and utilize Jinja-based DBT macros to promote code reusability, modularity, and dynamic SQL generation within DBT projects.
Data Transformation & Orchestration to Implement and manage data transformation pipelines using DBT, integrating with various data sources and ensuring efficient data flow.
Utilize advanced dbt concepts, including macros, materializations (e.g., incremental, view, table), snapshots, and configurations to build efficient data models.
Write highly optimized and complex SQL queries for data manipulation, cleaning, aggregation, and transformation within dbt models.
Implement and enforce best practices for dbt project structure, version control (Git), documentation, and testing.
Collaborate with data analysts, engineers, and business stakeholders to understand data requirements and translate them into effective data models (e.g., star schema, snowflake schema).
Design and implement logical and physical data models within dbt to support analytical and reporting needs.
Leverage Snowflake features and functionalities for performance optimization, including virtual warehouses, clustering, caching, and query optimization.
Manage and optimize data ingestion and integration processes from various sources into Snowflake.
Ensure data quality, integrity, and lineage throughout the data transformation process.
Implement and maintain DBT tests to ensure data quality, integrity, and adherence to business rules.
Implement and maintain data governance policies and procedures within the dbt environment.
Develop and execute automated tests for dbt models to ensure data accuracy and reliability.
Required Skills
Proven hands-on experience with dbt in a production environment, including extensive use of macros and advanced modeling techniques.
Expert-level proficiency in SQL for data querying, manipulation, and transformation.
Strong experience with Snowflake, including performance tuning and optimization.
Solid understanding of data warehousing concepts and ETL/ELT processes.
Experience with version control systems, particularly Git.
Familiarity with data modeling principles (star schema, snowflake schema).
Required Skills
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