Snowflake Data Engineer

Key Responsibilities:

Snowflake Engineering & Architecture

• Design and develop scalable data models, semantic layers, and Materialized Views within Snowflake to support complex downstream reporting and analytics.
• Write, test, and deploy highly optimized, complex SQL queries, stored procedures, and User-Defined Functions (UDFs).
• Leverage Snowpark (Python/Scala) for advanced data transformations and feature engineering directly within the Snowflake compute environment.
• Work with semi-structured and unstructured data formats (JSON, Parquet, XML) utilizing Snowflakes native capabilities (Variant data type, zero-copy cloning, time travel).

Performance Tuning & Cost Optimization

• Actively monitor and tune Snowflake query performance, identifying bottlenecks and optimizing execution plans.
• Manage and optimize Virtual Warehouse sizing, scaling policies, and clustering keys to ensure a balance of high performance and cost-efficiency.
• Implement effective caching strategies and data partitioning techniques for large-scale datasets.

Data Integration & Security

• Collaborate with integration teams to build seamless data pipelines using Informatica Intelligent Cloud Services (IICS) and AWS cloud services into Snowflake.
• Implement and enforce strict data security models, including Role-Based Access Control (RBAC), Row-Level Security, and Dynamic Data Masking, ensuring compliance with HIPAA, GDPR, and internal GxP policies.
• Participate in cross-team impact assessments to ensure schema evolutions or logic changes do not disrupt downstream consumers or existing data platforms.

Qualifications & Skills:

• Experience: 8 + years of overall IT experience in Data Engineering or Data Warehousing, with at least 3+ years of dedicated, hands-on experience developing in Snowflake.
• Certifications: Snowflake SnowPro Core Certification is required. SnowPro Advanced: Data Engineer certification is highly preferred.
• Technical Skills: * Expert-level proficiency in ANSI SQL and Snowflake-specific SQL extensions.
• Strong programming skills in Python (specifically for Snowpark and automation).
• Experience with cloud integration tools (IICS preferred) and foundational knowledge of AWS services (S3, EC2, IAM).
• Domain Experience: Prior experience working in the Life Sciences, Pharmaceutical, or Healthcare industry is highly advantageous, particularly with an understanding of GxP validation processes.
• Execution: Strong understanding of Agile methodologies, Jira, and modern DevOps practices for data platforms. Proven ability to translate complex business requirements into high-performing technical solutions.