Job Description & Details
This contract gig places you right at the intersection of modern data architecture and bleeding-edge AI capabilities within Snowflake. If you're tired of just building basic data pipelines and want to actually architect semantic layers, integrate Cortex AI, and build governed data products, this role is worth your attention.
What You'll Actually Be Doing
You will spend your days designing and refining enterprise-grade data layers that translate messy operational data into clean, governed, and business-friendly products. Expect to spend a lot of time mapping out target-state architectures, figuring out how to safely deploy Streamlit and Snowpark ML workloads, and setting up strict security controls like masking and RBAC. You'll be the bridge between raw data ingestion and advanced analytics applications, working closely with other technical SMEs to ensure the platform doesn't slow down as data volume scales.
The Core Tech Stack
You need a deep, production-level understanding of the Snowflake ecosystem far beyond basic SQL and warehouse sizing. The absolute must-haves for this role include mastering Snowflake Cortex Analyst, Cortex AI, Semantic Views, and the Model Registry. Because this is an architecture-heavy role, you also need to know how to implement robust governance frameworks, data lineage, and precise access control policies natively within Snowflake.
Interview Expectations
Be prepared for a hiring manager to drill down into your experience with semantic layers and AI integration by asking something like, "How would you design a governed semantic view using Cortex Analyst while ensuring strict row-level security for multi-tenant data?" They aren't looking for a textbook definition of RBAC; they want to hear about a time you actually handled conflicting security requirements and data performance bottlenecks in a live environment. Another favorite will likely revolve around Snowpark ML: expect them to ask how you manage model artifacts in the Model Registry and serve predictions efficiently without blowing up your warehouse credits.
Application Advice
To get past the ATS and grab the recruiter's attention, make sure your resume explicitly highlights your experience with advanced Snowflake features like Cortex, Snowpark ML, and Semantic Views rather than just traditional data warehousing. Don't just list these tools; describe specific projects where you designed target-state architectures or implemented strict security and governance frameworks. Weave in keywords like RBAC, data masking, lineage, and reusable data products to prove you can handle the enterprise-scale demands of this contract.