Lead the design and implementation of AI-powered analytics and applications using Snowflake Cortex. Develop semantic models, search and retrieval solutions, agents, AISQL workflows, Snowflake databases, and scalable ETL/ELT pipelines. Optimize performance, security, governance, and data quality while guiding high-impact initiatives and aligning data engineering solutions with organizational goals. Collaborate with technical and business stakeholders and provide executive guidance.
Core Responsibilities
AI & Snowflake Cortex Responsibilities
- AI Solution Design & Implementation: Build AI‑powered analytics, semantic insights, and business applications using Snowflake Cortex capabilities.
- Semantic Models & Views: Develop and maintain semantic layers enabling natural language querying, governed metrics, and business‑friendly data access.
- Cortex Search & Knowledge Retrieval: Design and optimize enterprise search solutions for document intelligence and knowledge retrieval.
- Cortex Agents: Configure and orchestrate agents to unify structured and unstructured data sources for automated workflows.
- AISQL Functions: Implement summarization, classification, extraction, sentiment analysis, and content generation use cases.
- AI Application Development: Build interactive AI applications using Streamlit, Snowsight, and Python frameworks within Snowflake.
- Testing & Improvement: Validate, monitor, and continuously enhance AI models, agents, and applications.
General Snowflake Development Responsibilities
- Database Design & Management: Create and manage Snowflake databases, schemas, tables, and objects for efficient, organized data storage.
- SQL Development: Write complex SQL queries to extract, transform, and load (ETL/ELT) data for analytics, reporting, and AI workflows.
- Data Pipeline Development: Build and maintain scalable ETL/ELT pipelines to ingest data from diverse sources into Snowflake with high quality and reliability.
- Performance Optimization: Monitor and optimize Snowflake performance through query tuning, clustering, micro‑partitioning, and workload scaling.
- Security & Access Control: Implement RBAC, data governance, user permissions, and security policies to protect sensitive information.
- Collaboration: Work closely with data engineers, analysts, architects, and business teams to translate requirements into scalable data and AI solutions.
- Testing & Documentation: Conduct unit testing, code reviews, and maintain clear documentation for data workflows, pipelines, and AI applications.
Required Skills & Experience
Snowflake & AI Expertise
- Hands‑on experience with Snowflake Cortex: Cortex Analyst, Cortex Search, Cortex Agents, AISQL Functions, Semantic Models.
- Strong understanding of Snowflake’s CoCO, Snowpark, and platform‑native AI capabilities.
Technical Skills
- Proficiency in SQL, Python, and ETL/ELT tools ( Informatica, dbt etc.).
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Familiarity with Spark, Kafka, and modern data engineering frameworks.
Data Warehousing & Modeling
- Strong knowledge of dimensional modeling(star Schema), semantic modeling, data architecture, and analytical data design.
- Experience integrating AI/ML patterns into enterprise data platforms.
Generative AI & LLMs
- Experience with prompt engineering, RAG architectures, embeddings, and agent design.
- Understanding of LLM‑driven workflows and enterprise AI application patterns.
Soft Skills
- Strong problem‑solving abilities and analytical thinking.
- Effective communication with technical and non‑technical stakeholders.
- Ability to work collaboratively and take ownership of projects.
Certifications (Preferred)
- Snowflake Certified Developer / SnowPro
- Cloud certifications (AWS, Azure, GCP)
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