We are seeking a Snowflake Cloud Architect with a minimum of 5 years of experience in Snowflake architecture, database design, data sharing, cost optimization, and API integration. This position requires an expert who is proficient in Snowflake's capabilities and best practices with a deep understanding of performance optimization, data modeling, and cloud data architecture principles. This role requires a highly skilled individual who can work independently under limited supervision while applying creativity and initiative to solve complex problems. The role requires strong problem-solving skills, a results-driven mindset, and a solid grasp of data governance and security practices in a cloud environment. The ability to collaborate with cross-functional teams and provide technical leadership is essential. This position will report to the Data Management Officer.
Assess the current infrastructure and database designs in Snowflake and come up with an optimized approach for the long-term sustainability of the environment.
Responsible for developing, optimizing, and overseeing the company's logical, conceptual, and physical data model and providing recommendations.
Lead user requirements elicitation for end-to-end Data integration process using ETL for Structured, semi-structured, and Unstructured Data.
Build robust data pipelines to ingest data into Snowflake, especially large datasets like Geometric files, GIS datasets, HEC-RAS models
Develop Near real-time data loads from various sources to Snowflake databases.
Proficient in Python, and Python libraries to assist businesses in developing machine learning and other scientific models using Snowflake, Streamlit, and Snowpark.
Develop cost optimization techniques to keep costs in control and develop future estimates as per the projected workloads and storage needs.
Contribute toward developing a comprehensive data cloud strategy for the agency, hybrid cloud infrastructure using Snowflake, AWS S3 and AWS RDS, AWS Kinesis, etc.,
Develop data-sharing functionalities using Snowflake APIs or other API techniques or tools to move data in and out with external entities and the public in a secure way.
Build artifacts to efficiently manage data science model life cycle, including development, testing, training, and deploying models in an efficient way and extended ad-hoc support.
Develop training modules and provide training support for the staff as needed.