Snowflake Data Engineer Offline

About the Role:
We are seeking a talented Snowflake Data Engineer to join our team and play a pivotal role in developing robust data pipelines and ETL processes. Your work will focus on integrating structured and unstructured data to power Generative AI (GenAI) use cases, including enabling CustomGPTs. You will work at the intersection of cutting-edge data engineering and AI-driven innovation, helping to unlock new possibilities for our products and services.

Key Responsibilities:

• Design, develop, and optimize scalable ETL pipelines for structured and unstructured data using Snowflake and other relevant tools.
• Implement and maintain data integration workflows to ensure smooth and efficient data ingestion, transformation, and delivery.
• Collaborate closely with the AI and Data Science teams to enable GenAI use cases, focusing on creating reliable and high-quality datasets.
• Build custom connectors and tools to facilitate data accessibility for CustomGPTs and other AI-driven applications.
• Ensure data accuracy, security, and compliance throughout the engineering process.
• Monitor and enhance the performance of Snowflake solutions, optimizing storage, queries, and resource utilization.
• Work with cross-functional teams to design data solutions aligned with business and technical requirements.

Required Qualifications:

• Strong experience with Snowflake architecture, development, and optimization.
• Proficiency in SQL and hands-on experience with ETL tools .
• Expertise in handling structured and unstructured data, including JSON, Parquet, or similar formats.
• Familiarity with cloud platforms such as AWS, Azure, or GCP and their data services.
• Understanding of Generative AI concepts and practical experience supporting AI/ML workloads.
• Knowledge of Python, Scala, or Java for data processing and transformation.
• Experience in creating or supporting CustomGPTs or similar AI models is a plus.
• Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.

Preferred Qualifications:

• Familiarity with streaming data pipelines using tools like Kafka or Spark.
• Background in data governance and implementing security best practices.
• Experience with APIs for data integration and ingestion.
• Demonstrated ability to communicate complex technical ideas to non-technical stakeholders.