Snowflake Data Lead/ Architect

Posted 5 Days Ago
Be an Early Applicant
New York, NY, USA
In-Office
Expert/Leader
Big Data • Cloud • Analytics • Consulting
The Role
Designs and leads enterprise Snowflake data architectures, cloud data platforms, ELT/ETL pipelines, and AI-powered applications. Builds RAG, semantic search, Cortex Agents, vector embedding, and Cortex AI Function solutions using Snowpark, Python, SQL, and dbt. Establishes secure, governed, and cost-optimized data environments, mentors engineering teams, leads architecture reviews, and partners with stakeholders on scalable data and generative AI solutions.
Summary Generated by Built In
DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.
 
We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.
Role: Snowflake Lead Data Engineer/ Architect

Location: NYC, NY

Full time role

 Job Description: 

We are seeking an experienced Snowflake Data Architect with expertise in Snowflake Cortex AI to design, architect, and implement modern cloud data platforms and AI-powered analytics solutions. The ideal candidate will have strong experience in Snowflake architecture, data engineering, and Generative AI capabilities such as RAG (Retrieval-Augmented Generation), Semantic Search, Cortex AI Functions, Cortex Agents, and Snowpark to deliver scalable, secure, and intelligent data solutions. Snowflake Cortex enables AI applications, semantic search, AI functions, and agentic workflows directly within Snowflake while keeping data governed inside the platform.
Key Responsibilities
  • Design enterprise-scale data architectures using Snowflake.
  • Lead end-to-end implementation of Snowflake Data Cloud solutions.
  • Architect modern data warehouses, data lakes, and Lakehouse solutions.
  • Design scalable ELT/ETL pipelines using Snowpark, SQL, Python, and dbt.
  • Build AI-powered data products using Snowflake Cortex AI.
  • Develop Retrieval-Augmented Generation (RAG) solutions using Cortex Search and vector embeddings.
  • Implement Semantic Search and enterprise knowledge retrieval solutions.
  • Design and deploy Cortex Agents and multi-agent AI workflows.
  • Develop AI-powered data applications using Cortex AI Functions (AI_COMPLETE, AI_CLASSIFY, AI_FILTER, AI_SUMMARIZE, AI_TRANSLATE, etc.).
  • Design secure AI architectures with RBAC, masking policies, row/column-level security, and governance.
  • Optimize Snowflake performance, storage, clustering, and cost.
  • Build metadata-driven and reusable data frameworks.
  • Collaborate with business stakeholders to translate requirements into scalable data and AI solutions.
  • Mentor engineering teams and establish architecture best practices.
Required Skills
  • 10+ years of Data Engineering/Data Architecture experience.
  • 5+ years of hands-on Snowflake implementation experience.
  • Strong expertise in:
    • Snowflake Architecture
    • Snowflake Data Cloud
    • Snowpark (Python/Scala)
    • SQL
    • Data Modeling (Dimensional & Data Vault)
    • ELT/ETL Design
  • Hands-on experience with Snowflake Cortex AI:
    • Cortex AI Functions
    • Cortex Search
    • Cortex Agents
    • RAG Architecture
    • Semantic Search
    • Vector Embeddings
    • Prompt Engineering
    • LLM Integration
  • Experience with Structured and Unstructured Data.
  • Experience building enterprise AI applications on Snowflake.
  • Strong understanding of Data Governance, Security, and AI Governance.
  • Experience with CI/CD and DevOps.
  • Strong communication and stakeholder management skills.
Nice to Have
  • Capital Markets, Banking, or Financial Services experience.
  • Experience with PostgreSQL, Oracle, SQL Server, or DB2 migrations.
  • dbt
  • Apache Iceberg
  • Kafka
  • Airflow
  • Talend
  • Denodo
  • Azure, AWS, or GCP
  • Databricks
  • Terraform
  • Docker & Kubernetes
  • REST APIs
  • LangChain or similar GenAI orchestration frameworks
Preferred Qualifications
  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
  • Snowflake SnowPro Advanced Certifications.
  • Cloud certifications (AWS, Azure, or GCP).
  • AI/ML or Generative AI certifications are a plus.
Preferred Experience
  • Designing enterprise-scale Snowflake platforms.
  • Implementing AI-driven analytics and intelligent search solutions.
  • Building production-grade RAG applications.
  • Architecting semantic layers and enterprise knowledge retrieval.
  • Delivering AI-powered data products with strong governance and security.
  • Leading architecture reviews, technical strategy, and client engagements.


Requirements
  • Snowflake
  • Snowflake Cortex AI (RAG, Semantic Search, Cortex Agents, AI Functions)
  • Snowpark (Python)
  • SQL
  • Data Modeling
  • Data Architecture
  • Cloud (AWS/Azure/GCP)
  • Strong communication and client-facing experience


Benefits
Full-time

Skills Required

  • 10+ years of data engineering or data architecture experience
  • 5+ years of hands-on Snowflake implementation experience
  • Strong Snowflake architecture and Snowflake Data Cloud expertise
  • Experience with Snowpark using Python or Scala
  • Strong SQL skills
  • Experience with dimensional and Data Vault modeling
  • Experience designing ELT and ETL solutions
  • Hands-on Snowflake Cortex AI experience, including Cortex AI Functions, Cortex Search, Cortex Agents, RAG, semantic search, vector embeddings, prompt engineering, and LLM integration
  • Experience with structured and unstructured data
  • Experience building enterprise AI applications on Snowflake
  • Strong understanding of data governance, security, and AI governance
  • Experience with CI/CD and DevOps
  • Strong communication and stakeholder management skills
  • Strong communication and client-facing experience
  • Capital markets, banking, or financial services experience
  • Experience with PostgreSQL, Oracle, SQL Server, or DB2 migrations
  • Experience with dbt
  • Experience with Apache Iceberg, Kafka, Airflow, Talend, or Denodo
  • Experience with AWS, Azure, or GCP
  • Experience with Databricks, Terraform, Docker, or Kubernetes
  • Experience with REST APIs
  • Experience with LangChain or similar generative AI orchestration frameworks
  • Bachelor’s or master’s degree in computer science, information technology, or a related field
  • Snowflake SnowPro Advanced Certification
  • Cloud certification in AWS, Azure, or GCP
  • AI/ML or generative AI certification
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The Company
414 Employees
Year Founded: 2018

What We Do

DATAECONOMY is a global, cloud-first data and AI consultancy delivering enterprise-grade solutions through an innovative intellectual-property suite. Its work spans data and BI platform modernization, self-service AI, data mesh and fabric, master data management, governance, cloud enablement, digital engineering, knowledge graphs, and machine lakes supporting cybersecurity and financial-crime use cases for enterprise clients.

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