Senior Director, Analytics Engineering, Data Analytics & AI
Snowflake · US-CA-Menlo Park
About this role
**About Snowflake** At Snowflake, we’re powering the era of the agentic enterprise. We’re looking for AI-native thinkers who treat AI as a high-trust collaborator—curious, low-ego, and energized by reinventing how work gets done. **Role: Senior Director, Analytics Engineering** Join our Data, Analytics, and AI organization (DAA) and report directly to the Chief Data & Analytics Officer. You’ll lead a team of 20+ Analytics Engineers building and operating pipelines behind Snowflake’s revenue, bookings, people analytics, and go-to-market reporting within our governed data platform. **Location / Schedule** This role has an in-office requirement: you must be able to work out of our Menlo Park office **at least 3 days per week**. --- **In this role you will** - **Lead and grow the Analytics Engineering organization**: Manage through direct reports (team leads/managers), set priorities, and define technical strategy. - **Drive internal data transformation**: Build an AI-ready data foundation with strong emphasis on documentation, contracts, context, and governance. - **Own Snowflake’s internal analytics agents**: Build, improve, and maintain general-purpose analytics agents, including context and semantic layers (with evals, orchestration instructions, and ground-truth datasets). - **Champion AI-assisted engineering**: Drive adoption of Cortex Code-based agentic workflows and reusable skills to accelerate common Analytics Engineering work (e.g., model development, PR review, root-cause analysis). - **Be Snowflake’s customer zero**: Act as the first trusted tester of Snowflake features across the data engineering and transformation stack; partner closely with Product and Engineering. - **Represent Snowflake**: Support GTM and Frontier Engineering through customer conversations, speaking engagements, and thought leadership. - **Continually push the stack forward**: Adopt the latest internal Data and AI capabilities and expand what’s possible on Snowflake. - **Partner cross-functionally**: Serve as the primary escalation point for business stakeholders; drive a common roadmap and transform upstream workflows with data in mind. - **Represent your teams upward and cross-org**: Share patterns and learnings to advance broader technical initiatives across DAA. --- **What you will need** - **10+ years** of experience in analytics engineering, data engineering, or data architecture, including **second-line leadership** experience managing managers or senior ICs across multiple teams. - Strong **systems thinking**: design for second-order effects across models, pipelines, and architecture. - Deep expertise in **Snowflake**: data modeling, data governance (e.g., RBAC, row access policies, masking policies), and Snowflake capabilities (Dynamic Tables, Streams, Tasks, Horizon, Cortex). - **Expert-level dbt**: macro development, testing, CI/CD frameworks, and large-scale multi-team project management. - Hands-on experience with **Airflow** (or similar orchestration platforms). - Proven ownership of **finance- or revenue-critical** deadline-driven pipelines where accuracy and auditability are non-negotiable. - Familiarity with **GTM/sales analytics** domains (e.g., master data management, consumption & attainment pipelines, quota/territory data). - Advanced adoption of **AI-assisted engineering tools** (e.g., Cortex Code, Claude Code), including agentic skill development and prompt engineering for data workflows. - Track record driving large-scale data
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