Snowflake dbt Engineer

Must Have Technical/Functional Skills

Mandatory Technical skills - Snowflake, dbt, SQL, Python, Data Engineering, Data Modeling
• 5+ years of overall Data Engineering experience.
• 3+ years of hands-on Snowflake development experience in production environments.
• 2+ years of hands-on dbt Core or dbt Cloud development experience.
• Strong hands-on experience with Advanced SQL, ELT/ETL pipelines, data modeling, performance tuning, and production support.
• Recent coding and development experience is mandatory. Profiles that are mainly architecture-focused should not be considered.

Roles & Responsibilities
• Design, develop, test, deploy, and support ELT pipelines using Snowflake and dbt.
• Build dbt models across staging, intermediate, and mart layers using reusable and maintainable development standards.
• Create and manage dbt incremental models, snapshots, tests, documentation, sources, seeds, macros, and packages.
• Develop Snowflake objects including databases, schemas, tables, views, secure views, streams, tasks, and Snowpipe pipelines.
• Write and optimize complex SQL queries, stored procedures, and transformation logic.
• Perform source-to-target mapping and implement transformation rules based on business and technical requirements.
• Build dimensional data models, data marts, facts, dimensions, and analytics-ready datasets.
• Implement data quality checks, reconciliation controls, exception handling, and monitoring mechanisms.
• Troubleshoot production data issues, pipeline failures, performance bottlenecks, and data discrepancies.
• Optimize Snowflake warehouse usage, query performance, clustering, and cost efficiency.
• Work with business analysts, data architects, application teams, and reporting teams to deliver trusted data products.
• Support CI/CD and DataOps practices for Snowflake and dbt deployments Education: Bachelors degree

Salary Range: $100000 - 120000 a year

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