Snowflake Data Engineer - W2 , No C2C

Snowflake Data Engineer - W2 Only, No C2C - 8+YEARS

We are seeking a Snowflake Data Engineer to design, build, and optimize scalable data solutions on the Snowflake Data Cloud.

This role will support analytics, reporting, and AI/ML initiatives across commercial, manufacturing, R&D, and quality systems.

The ideal candidate has strong expertise in cloud data engineering, ELT pipelines, and enterprise-grade data platforms within regulated environments.

• Bachelor’s degree in computer science, Engineering, Data Science, or related field
• 8+ years of hands‑on experience in data engineering with strong focus on Snowflake Data Warehouse design and management
• Extensive experience designing, building, and managing enterprise‑scale Snowflake data warehouses
• Strong hands‑on experience with Snowflake (SQL, Virtual Warehouses, Snowpipe, Streams, Tasks, Time Travel, Zero Copy Cloning)
• Proven expertise in Snowflake warehouse management
  , including sizing, multi‑cluster warehouses, workload isolation, concurrency scaling, and cost optimization
• Proficiency in SQL and Python for data transformations and orchestration
• Experience with cloud platforms:
  AWS
  , Azure
  , or GCP
• Experience building robust ELT pipelines and working with structured and semi‑structured data (JSON, Parquet, Avro)
• Strong knowledge of data modeling for data warehouses (star/snowflake schemas, dimensional modeling)
• Experience implementing data governance, security, and access controls in Snowflake (RBAC, masking policies, row access policies)
• Experience with Git-based version control and CI/CD pipelines

• Design, develop, and maintain scalable data pipelines using Snowflake as the core data platform
• Build and optimize ELT workflows using tools such as dbt
  , Airflow
  , Matillion
  , or Fivetran
• Implement data models (star/snowflake schemas) to support analytics, BI, and advanced analytics use cases
• Optimize Snowflake performance and cost (warehouses, clustering, caching, resource monitors)
• Integrate data from diverse sources: ERP (SAP), CRM (Salesforce), manufacturing systems, LIMS, IoT, and external data feeds
• Ensure data quality, governance, lineage, and metadata management in compliance with regulatory standards (GxP, FDA, ISO)
• Collaborate with data analysts, data scientists, product teams, and business stakeholders
• Implement CI/CD, version control, and automated testing for data pipelines
• Support data security, access controls, and compliance requirements
• Participate in architecture reviews and contribute to enterprise data strategy