- Job Role: Data Engineering-Cloud Data Engineering
- Experience (In Years): 9-12
- Job Location: Delaware/Wilmington
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)
Responsibilities
Oversee organizational data engineering solutions. Lead highimpact initiatives. Ensure alignment with organizational goals. Provide executive guidance.
Qualifications
Graduate in Computer Science, Data Science, or related field. 6-8 years of experience in data engineering or related field.
