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Snowflake is seeking a Senior Director of Analytics Engineering to lead a team of 20+ Analytics Engineers within the Data, Analytics, and AI (DAA) organization, reporting directly to the Chief Data & Analytics Officer. This is a hands-on leadership role focused on building and operating the data pipelines that power Snowflake's revenue, bookings, people analytics, and go-to-market reporting.
Key responsibilities include:
- Leading and growing the Analytics Engineering organization through direct reports (team leads/managers), setting priorities and technical strategy
- Driving Snowflake's internal data transformation with emphasis on documentation, governance, and AI-readiness
- Owning Snowflake's internal analytics agents, including building and maintaining general-purpose agents, semantic layers, and evaluation frameworks
- Championing AI-assisted engineering by driving adoption of Cortex Code-based agentic workflows across teams
- Serving as Snowflake's "customer zero" for internal data and AI features, providing early feedback to Product and Engineering teams
- Representing Snowflake externally through customer conversations, speaking engagements, and thought leadership
- Pushing the technical stack forward by adopting latest Data and AI capabilities
- Partnering cross-functionally with business stakeholders and serving as escalation point for data-related initiatives
- Contributing team patterns and learnings to broader DAA organizational initiatives
The role requires a minimum of 3 days per week in-office at the Menlo Park headquarters.
REQUIREMENTS:
- 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
- Systems thinking mindset with ability to see connections between data models, pipelines, and architectural decisions
- Deep expertise in Snowflake including data modeling, data governance (RBAC, row access policies, masking policies), Dynamic Tables, Streams, Tasks, Horizon, and Cortex
- Expert-level dbt skills including macro development, testing, CI/CD frameworks, and large-scale multi-team project management
- Hands-on experience with Airflow or similar orchestration platforms
- Track record owning finance- or revenue-critical, deadline-driven data pipelines with non-negotiable accuracy and auditability requirements
- Familiarity with GTM and sales analytics domains including 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
- Record of driving large-scale data transformation initiatives across complex organizations
- Experience with downstream BI/consumption layers such as Streamlit, Sigma, or Tableau
- Comfort with Jira/Confluence-based agile delivery models
- Excellent written and verbal communication skills with track record of writing technical specs and stakeholder-facing materials for non-technical audiences
