# Senior Director, Analytics Engineering, Data Analytics & AI at Snowflake

- Company: Snowflake
- What the company does: Snowflake powers AI, data engineering, applications, and analytics on a trusted, scalable AI Data Cloud—eliminating silos and accelerating innovation. Backed by Sequoia.
- Company website: https://www.snowflake.net/
- Type: Startups (AI role)
- Level: Principal and up
- Location: US-CA-Menlo Park
- Work setup: On-site
- Pay: $292K to $383K base salary per year (USD)
- Posted: 2026-09-19
- Apply by: 2026-11-03
- Apply: https://jobs.ashbyhq.com/snowflake/517c85f9-9b37-4510-a969-978671021376
- Page: https://www.1752.vc/careers/jobs/snowflake-senior-director-analytics-engineering-data-analytics-and-ai/

## About the role

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.

## What they're looking for

- 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

Tags: Data Analytics and AI