Data Engineer

Summary:

Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.

Key Responsibilities:

Snowflake Architecture & Engineering:

• Lead and implement Snowflake solutions across data ingestion, storage, transformation, and access.
• Lead end-to-end implementation of solutions using Snowflake’s latest features.
• Develop reusable frameworks, UDFs, and components using Snowpark or SQL scripting.
• Develop performance-optimized pipelines using Snowflake-native capabilities and modern ELT tools.
• Establish data governance, security models, RBAC, and masking policies in line with compliance standards.
• Conduct performance tuning, workload monitoring, and optimization.

GenAI:

• Enable GenAI use cases leveraging Snowflake’s native capabilities
• Implement Cortex AI features with custom workflows and business logic

Required Qualifications and Certifications:

• 8+ years of experience as a Snowflake Lead or Data Engineer.
• Good command of Snowflake internals, including performance tuning, clustering, caching.
• Good Knowledge of SQL, Snowflake scripting, and at least any one cloud platforms (AWS, Azure, or GCP).
• Knowledge of Advanced Features like dynamic tables, Snow pipe streaming, Snowflake Cortex AI etc.
• Good communication skills with the ability to bridge technical and business discussions.
• Certifications: SnowPro Core Certified.
• Minimum 2 year(s) of experience is required