Senior Director, Analytics Engineering, Data Analytics & AI

Snowflake
Menlo Park
Workplace: OnsiteFull timeUSD 292,000 - 383,250 annuallyFunction: Data Analytics & Business IntelligenceSkills: ["Systems thinking","Leadership","Technical writing","Stakeholder management","Communication","Cross-functional collaboration","Strategic prioritization"]

Lead Snowflake’s Analytics Engineering organization within the Data, Analytics, and AI team, managing 20+ engineers who build and run governed data pipelines powering revenue, bookings, people analytics, and GTM reporting. Drive internal data transformation toward an AI-ready foundation, build analytics agents with context and semantic layers, and promote AI-assisted engineering workflows (including Cortex Code). Partner with Product/Engineering, act as customer zero, and represent Snowflake with customers and thought leadership.

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Snowflake
Snowflake
1 day ago

Senior Director, Analytics Engineering, Data Analytics & AI

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Last checked: 4 hours agoStatus: Live

Job Summary

Lead Snowflake’s Analytics Engineering organization within the Data, Analytics, and AI team, managing 20+ engineers who build and run governed data pipelines powering revenue, bookings, people analytics, and GTM reporting. Drive internal data transformation toward an AI-ready foundation, build analytics agents with context and semantic layers, and promote AI-assisted engineering workflows (including Cortex Code). Partner with Product/Engineering, act as customer zero, and represent Snowflake with customers and thought leadership.
Location: Menlo Park
Workplace: Onsite
Employment Type: Full time
Job Function: Data Analytics & Business Intelligence
Seniority: Director level

Key Responsibilities

  • •Lead and grow the Analytics Engineering organization by managing through direct reports and setting priorities and technical strategy.
  • •Drive internal data transformation to create an AI-ready data foundation with strong documentation, contracts, context, and governance.
  • •Build, improve, and maintain general purpose internal analytics agents and underlying context/semantic layers, including evals, orchestration instructions, and ground truth datasets.
  • •Adopt and champion AI-assisted engineering workflows using Cortex Code-based agentic workflows and reusable skills to speed analytics engineering work.
  • •Act as customer zero by being the first trusted tester of Snowflake features across the data engineering/transformation stack, collaborating with Product and Engineering on roadmaps.

Pay and Benefits

Salary: USD 292,000 - 383,250 annually
Equity and Bonus:Equity

Key Requirements

  • •10+ years in analytics engineering, data engineering, or data architecture, with second-line leadership experience managing managers or senior contributors across multiple teams.
  • •Lead through systems thinking across interconnected models, pipelines, and architectural decisions, designing for second-order effects.
  • •Deep expertise in Snowflake data modeling and governance (RBAC design, row access policies, masking policies) and core Snowflake features (Dynamic Tables, Streams, Tasks, Horizon, Cortex).
  • •Expert-level dbt skills, including macro development, testing, CI/CD frameworks, and managing large-scale, multi-team projects.
  • •Hands-on experience with Airflow (or similar orchestration) and a track record owning finance/revenue-critical, deadline-driven pipelines with accuracy and auditability; familiarity with GTM/sales analytics domains and AI-assisted engineering tools (Cortex Code, Claude Code).
Experience:Data engineeringAnalytics engineeringData architectureAIAgentic workflowsGo-to-market analyticsRevenue analyticsData governance
Skills:Systems thinkingLeadershipTechnical writingStakeholder managementCommunicationCross-functional collaborationStrategic prioritization
Tech Stack:SnowflakeDbtAirflowCortexCortex CodeClaude CodeDynamic TablesStreamsTasksHorizonRBACRow access policiesMasking policiesStreamlitSigmaTableauJiraConfluenceSemantic layersOrchestration

Company Brief

Snowflake
Provides a cloud-native data platform for data warehousing, data engineering, data science, and analytics, enabling organizations to store, process, and share large-scale data across multiple cloud providers with elastic scalability and performance.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Bozeman, United States
Founded: 2012
WebsiteLinkedIn