This is a W2 contract position; C2C and bench sales candidates will not be considered. Job Overview: We are seeking a seasoned Data Engineer with 6–8+ years of experience to support critical data initiatives and drive the development of scalable, high-performance data solutions. This role is ideal for someone with deep technical expertise in data pipeline engineering, Snowflake optimization, and secure data architecture. Key Responsibilities: • Design, build, and maintain scalable and efficient data pipelines. • Develop and manage data warehouses and data lakes for analytics and machine learning use cases. • Ensure data quality, integrity, and adherence to best practices. • Optimize data storage, access, and retrieval for performance and cost-efficiency. • Monitor and tune Snowflake environments for performance and credit usage. • Implement secure data sharing, row-level access policies, and data masking for sensitive information (e.g., PII, financial data). • Enforce robust role-based access controls (RBAC) within Snowflake. • Collaborate with data scientists, analysts, and cross-functional teams to support business goals. • Create semantic layers, aggregate tables, and governed data models (Star/Snowflake schemas) to enable scalable, business-friendly analytics. Required Qualifications: • 6–8+ years of hands-on experience in data engineering. • Strong expertise in SQL and scripting languages. • Proven experience with scalable ETL pipelines and scheduler tools. • Experience with CI/CD orchestration and automation (e.g., Jenkins, GitHub). • Deep knowledge of Snowflake, including performance tuning and secure data sharing. • Ability to build semantic data models and design analytics architectures. Preferred Qualifications: • Experience with Machine Learning, LLMs, or AI model development/deployment. • Strong written and verbal communication skills for cross-team collaboration.