Role Overview
Looking for an IT Professional with 9-14 years of hands-on Snowflake Data Cloud experience to lead the design, implementation, and optimization of scalable data solutions. The ideal candidate excels in Snowflake architecture, data warehousing, data lakes, serverless/cloud automation, and AI/LLM concepts.
In This Role, You Will:
Key Responsibilities
- Architect and deliver end-to-end data solutions on Snowflake.
- Demonstrate deep understanding of data warehousing concepts and work with structured, semi-structured, and unstructured data.
- Apply deep expertise in Snowflake architecture (compute, storage, security, data sharing).
- Use Snowflake native load utilities (e.g., Snowpipe, COPY INTO) for data ingestion and transformation.
- Develop and manage API-based integrations and automation.
- Lead data governance, quality, security, and compliance efforts.
- Optimize performance and manage costs.
- Oversee Snowflake infrastructure provisioning, scaling, and monitoring.
- Act as primary stakeholder contact; drive meetings and translate business needs.
- Foster innovation in data architecture, analytics, and AI-driven solutions.
- Collaborate with cross-functional teams.
- Stay current on Snowflake advancements, especially AI features like Cortex.
- Proactively perform POCs for new Snowflake features & drive adoptions.
- Leverage data lake frameworks & serverless technologies
Here's What You Need:
Required Skills & Qualifications
- Bachelor’s/master’s in computer science, IT, or related field.
- 8+ years of Snowflake Data Cloud experience.
- Deep understanding of Snowflake architecture and ecosystem.
- Strong grasp of data warehousing concepts and diverse data structures.
- Expertise in Snowflake native load utilities.
- API integration and automation experience.
- Data governance, security, and compliance background.
- Performance optimization and cost management skills.
- Experience with Snowflake infrastructure management.
- Excellent communication and stakeholder management.
- Innovative, AI-driven mindset.
- Hands-on Python for data engineering/automation.
- Knowledge of AI, LLMs, and Snowflake AI features (e.g., Cortex).
- Experience with data lake frameworks and serverless technologies.