Snowflake Data Engineer (DBT AWS)

Snowflake DE

Key Responsibilities

• Develop and maintain scalable data transformation pipelines using Snowflake and dbt.
• Design, build, and manage dbt models using staging, intermediate, and mart layers.
• Develop reusable dbt macros to standardize business logic and reduce code duplication.
• Write complex SQL queries involving joins, CTEs, window functions, aggregations, and analytical transformations.
• Optimize Snowflake queries, warehouses, and data models for performance and cost efficiency.
• Implement dbt tests, data quality validations, and documentation.
• Manage dbt sources, snapshots, incremental models, and dependencies.
• Follow best practices for code reviews, version control, CI/CD, and deployment.
• Collaborate with business analysts, data architects, and other engineering teams to translate business requirements into robust data solutions.
• Troubleshoot data pipeline failures and resolve data quality and performance issues.

Required Skills and Experience

• Strong hands-on experience with Snowflake data warehousing.
• Advanced SQL skills, including complex transformations, CTEs, joins, window functions, and query optimization.
• Practical experience developing dbt models, including incremental models and modular transformations.
• Experience creating and maintaining custom dbt macros using Jinja.
• Knowledge of dbt testing, sources, snapshots, seeds, schema YAML files, and documentation.
• Understanding of data modelling concepts, including dimensional modelling, star schemas, and slowly changing dimensions.
• Experience with Git, branching strategies, pull requests, and code reviews.
• Strong analytical and problem-solving skills.

Good to Have

• Experience with dbt Cloud or dbt Core.
• Familiarity with CI/CD automation for dbt deployments.
• Experience with orchestration tools such as Airflow.
• Knowledge of Snowflake performance optimization, query profiling, and warehouse sizing.
• Exposure to cloud platforms such as AWS, Azure, or GCP.