Data & Ai Solution Architect - Snowflake

Title: Data & AI Solution Architect - Snowflake

Location: Arlington, VA

Work Mode: Hybrid (3 days onsite must)

Positions: 2

Job Description

This is a hands-on Senior role at the intersection of data engineering, cloud architecture, and generative AI. You will serve as the primary technical authority on our Snowflake Data Cloud strategy, designing scalable, secure, and cost-efficient data platforms that underpin enterprise analytics, operational reporting, and AI-native applications. You will get hands-on with complex architectural problems while influencing direction at the executive level.

Key Responsibilities

Strategic planning and hands-on engineering of Snowflake/Big Data and cloud environments that support clients’ advanced analytics and data science initiatives.

Provide support in defining the scope and sizing of work.

Work closely with enterprise architects, information security teams, data management teams, and IT solution engineering teams to ensure the architected solution meets all customer needs from both functionality and IT perspectives.

Lead design efforts for data solutions including creation of artifacts such as diagrams, playbooks, and other technical documents.

Translate business requirements into technology solutions.

Mentor and guide Jr. team members to deliver solutions on time.

Create architecture blueprints and work with development teams to execute the vision.

Skills & Experience

Overall 10-15 years of experience in Solution Architecture, Data Management, Data Lake and Lakehouse design and development.

Snowflake (Expert): Virtual Warehouses, Snowpark, Cortex AI (LLM Functions, Vector Search, Document AI, Cortex Guard), Dynamic Tables, Streams & Tasks, Data Sharing.

Data Modeling (Expert): Data Vault 2.0, Kimball dimensional, hybrid schemas;
conceptual, logical, and physical design for analytics and AI workloads.

dbt (Advanced): Core and Cloud, modular transformation layer design, testing frameworks, and CI/CD integration with Snowflake.

Python / Snowpark (Proficient): Custom UDFs, ML pipelines, data transformation logic running natively inside Snowflake compute.

RAG & GenAI (Proficient): End-to-end pipeline design including chunking, embeddings, vector search, LLM integration, source citation, and output validation.

Cloud (Advanced):

AWS (S3, Glue, Step Functions)

Azure (Data Factory, Key Vault, Synapse)

GCP (Dataflow, Composer, BigQuery)

Data Integration: Fivetran, Airbyte, Kafka, SnapLogic;
batch and streaming ingestion patterns at enterprise scale.