Overview

We are seeking an expert-level U.S based Snowflake Contractor for client-facing engagements. This role requires a blend of advanced data science, strategic data architecture and hands-on data engineering. You will act as a trusted advisor, guiding our clients in architecting and optimizing their Snowflake instance, building reliable, single source of truth and leveraging it to deploy advanced AI/ML models (using Snowflake AI Cortex) and making data available to power marketing workflows into downstream technologies like HubSpot and Salesforce. 

Responsibilities

• Data Architecture & Modeling: Architect and build future-state Customer Data Warehouse (CDW) solutions within Snowflake. Design and implement data governance frameworks, data quality checks, and comprehensive metric dictionaries.
• Data Mobility & Integration: Design and implement robust, scalable data mobility (ETL/Reverse ETL) pipelines connecting Snowflake with key platforms like HubSpot, Salesforce, and other MarTech systems.
• AI/ML & Data Quality Implementation: Develop and deploy AI/ML models within Snowflake using Snowflake AI Cortex and Snowpark. This includes building solutions for data quality (e.g., deduplication, entity resolution) and business analytics.
• Marketing Segmentation & Activation: Design and build sophisticated marketing segmentation models (persona, behavioral, etc.) and orchestrate the delivery of these audiences to client activation platforms.
• Client Advisory: Act as the primary Snowflake technical advisor, translating complex technical and architecture challenges for data and marketing teams.

Qualifications

• Data Science Fundamentals: Strong background in statistical analysis, machine learning, data wrangling, and data storytelling.
• Snowflake Expertise: Mastery of the Snowflake platform, including its core architecture, Snowpark, Snowsight, and governance features.
• Snowflake AI/ML: Direct, hands-on experience using Snowflake AI Cortex (Cortex AI, LLM Functions) to build and deploy machine learning models.
• Data Architecture & Strategy: Deep knowledge of CDW principles, advanced data modeling techniques, and data governance best practices.
• Core Technical Stack:
  • Expert-level Advanced SQL (window functions, CTEs, complex joins).
  • Strong Python proficiency for data science (Pandas, NumPy, scikit-learn, SciPy).
• Marketing & Sales Tech Ecosystem: Hands-on experience with the data structures and integration patterns of platforms like HubSpot, Salesforce, 6sense, ZoomInfo, and Reverse ETL tools.
• Cloud Environments: Familiarity with AWS, GCP, or Azure (particularly as they relate to Snowflake integration).