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Menlo Park, California, United States
Hybrid
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.
Snowflake is about empowering enterprises to achieve their full potential with Data & AI. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology and careers to the next level.
We're hiring for a Senior Director of Analytics Engineering to join our Data, Analytics, and AI organization (DAA), reporting directly to the Chief Data & Analytics Officer. You will lead a team of 20+ Analytics Engineers that build and operate the pipelines behind Snowflake's revenue, bookings, people analytics, and go-to-market reporting within our governed data platform.
This role has an in-office requirement — you must be able to work out of our Menlo Park office a minimum of 3 days a week.
Lead and grow the Analytics Engineering organization: Manage through your direct reports (team leads/managers), setting priorities and technical strategy across the team.
Drive Snowflake’s internal data transformation: Lead your teams' ongoing work to create an AI ready data foundation, with an emphasis on documentation, contracts, context, and governance.
Own Snowflake’s internal analytics agents: Build, improve, and maintain general purpose analytics agents - and underlying context and semantic layers - that can be used across the organization including evals, orchestration instructions, and ground truth data sets
Champion AI-assisted engineering: Drive adoption of Cortex Code-based agentic workflows and reusable skills across your teams to speed up typical Analytics Engineering jobs-to-be-done, including model development, PR review, and root-cause analysis.
Act as Snowflake’s customer zero: Be the first trusted tester of Snowflake’s own features across the data engineering and transformation stack, deeply engaging with Product and Engineering teams on product and feature roadmaps
Represent Snowflake: Support our GTM and Frontier Engineering teams by joining customer conversations, supporting speaking engagements, and publishing thought leadership, ultimately demonstrating the art of possible on Snowflake to all our customers and prospects
Continually push our stack forward: Push the boundaries of what we can accomplish on Snowflake, adopting the latest internal Data and AI capabilities.
Partner cross-functionally: Serve as the primary point of escalation for business stakeholders, driving towards a common roadmap and transforming upstream processes and workflows with data in mind
Represent your teams upward and cross-org: Contribute your teams' patterns and learnings to the Data, Analytics, and AI org's broader technical initiatives
10+ years of experience in analytics engineering, data engineering, or data architecture, including second line leadership experience managing managers or senior individual contributors across multiple teams.
A systems thinker at your core: You naturally see how individual data models, pipelines, and architectural decisions connect — and you design for second-order effects, not just the immediate problem.
Deep expertise in Snowflake, including data modeling, data governance (e.g., RBAC design, row access policies and masking policies), and the broader Snowflake feature set (Dynamic Tables, Streams, Tasks, Horizon, Cortex)
Expert-level dbt skills, including macro development, testing and CI/CD frameworks, and large-scale multi-team project management.
Hands-on experience with Airflow or similar orchestration platforms
A track record owning finance- or revenue-critical, deadline-driven data pipelines where accuracy and auditability are non-negotiable.
Familiarity with GTM and sales analytics domains: master data management, consumption & attainment pipelines, quota/territory data.
Advanced adoption of AI-assisted engineering tools — Cortex Code, Claude Code, or similar agent frameworks — including agentic skill development and prompt engineering for data workflows.
A record of driving large scale data transformation initiatives across complex organizations
Experience with downstream BI/consumption layers such as Streamlit, Sigma, Tableau, etc.
Comfort working in a Jira/Confluence-based agile delivery model.
Excellent written and verbal communication skills, with a track record of writing clear technical specs and stakeholder-facing materials for non-technical audiences
Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
