Senior Data Analytics Engineer

Snowflake•Menlo Park, CA

About The Position

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are hiring a Senior Data Analytics Engineer for our Data Analytics and AI team. We own Snowflake's internal data platform, powering analytics across Finance, Sales, and HR, and we're looking for someone to help shape what's possible for the teams who rely on it every day.

Requirements

8+ years of experience in analytics engineering, data architecture, or related roles, or equivalent experience
Deep expertise in Snowflake, including advanced data modeling, RBAC design, performance optimization, and the broader feature set (Cortex, Dynamic Tables, Streams, Tasks)
Expert-level dbt skills (dbt Core and/or dbt Platform), including macro development, testing frameworks, CI/CD integration, and large-scale project management
Strong proficiency with AI development tools, including LLM-powered workflows, agent frameworks (Cortex Agents, Claude Code, Cortex Code), and prompt engineering for data use cases
Experience designing and implementing RBAC frameworks at scale, including row access policies, masking policies, and role hierarchies in Snowflake or similar platforms
Excellent written and verbal communication skills, with a track record of writing clear technical specs, architecture documents, and stakeholder-facing materials
Demonstrated ability to operate with principal-level scope: driving cross-functional initiatives, influencing without authority, and delivering outcomes across multiple teams

Nice To Haves

Experience working at a technology company with a large-scale internal data platform
Familiarity with Python for data pipeline development, scripting, and automation
Experience presenting technical content to external audiences (customers, conferences)
Experience with Snowflake Cortex AI or GenAI-native data tooling in production environments

Responsibilities

Shape the architecture and design principles for Snowflake's internal data platform, owning decisions that affect how data flows, is governed, and accessed across Finance, Sales, HR, and other business-critical functions
Lead cross-functional data initiatives from problem framing through delivery, aligning stakeholders across Engineering, Analytics, and Business Systems on what to build and why
Define and enforce RBAC frameworks, row access policies, and masking policies at scale, ensuring the right data reaches the right people with appropriate governance controls
Drive adoption of AI-assisted data workflows by integrating LLM-powered tools, Cortex Agents, and automation capabilities into the team's data engineering practice
Set the technical standard for dbt at scale, defining modeling conventions, testing frameworks, and CI/CD practices adopted by the full data team
Influence without authority across teams by writing architecture docs, technical specs, and stakeholder-facing materials that drive alignment and accelerate delivery
Identify and resolve systemic data quality, performance, and reliability issues, raising the bar for what "done" looks like on the platform