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Protocol Intelligence
Data-driven signals on your job's competitivenessMetro-based Lead Data Engineer with common title but specialized Snowflake/dbt skills yields medium competition.
Snowflake, dbt and AWS skills are transferable across industries but require cloud-platform experience, so medium.
Explicit 8–10 years plus mandatory Snowflake, dbt, AWS, SQL, and Python makes shortlisting highly strict.
Job Description
Structured overview of role & requirementsAbout This Role
Develop, maintain, and optimize scalable dbt models and ETL/ELT data pipelines within Snowflake and AWS environments.
Administer Snowflake data warehouses including security configurations and governance alignment with data quality standards.
Manage AWS services integration and CI/CD pipeline implementation for reliable cloud data infrastructure and automated deployments.
Minimum Requirements
8-10 years of experience in data engineering with hands-on expertise in Snowflake, dbt, and AWS cloud services.
Advanced proficiency in SQL and Python for data engineering and automation.
Bachelor’s or Master’s degree in Computer Science, IT, Engineering, or a related field.
Experience administering Snowflake warehouses including databases, schemas, roles, and security; experience with AWS services such as S3, Lambda, Secret Manager, IAM, and CloudWatch.
Ideal Candidate Profile
Experienced in managing complex, large-scale ELT pipelines and optimizing data warehouse performance for cost and speed.
Capable of collaborating with governance teams to ensure certification and quality-gate standards for data models.
Ability to diagnose production issues and maintain documentation for maintainability and downstream support.