Snowflake Data Engineer – Semantic Layer & Analytics Engineering.
Must skills: Medallion Architecture (bronze - silver - gold) with cortex ai
Role Overview
hands-on Snowflake Data Engineer to help design, build, and optimize scalable data pipelines and semantic models. This role goes beyond ticket execution and requires strong ownership across architecture, implementation, documentation, and production support.
Key Responsibilities
Design and develop scalable data pipelines in Snowflake.
Design , build and maintain dimensional models, Gold datasets, and semantic layers.
Optimize query performance, data quality, and platform efficiency.
Implement CI/CD practices for data engineering workflows.
Collaborate with analytics, BI, and business teams to define data requirements.
Create technical documentation and operational runbooks.
Provide production support, troubleshooting, and continuous improvement.
Required Qualifications
Strong experience with Snowflake and modern data engineering practices.
Expertise in SQL, data modeling, ETL/ELT, and analytics engineering.
Experience building semantic layers and business-ready datasets.
Familiarity with CI/CD, version control, and data quality frameworks.
Strong problem-solving, communication, and stakeholder management skills.
Work Location: In person
