Data Analytics Lead — AI-Driven Executive Insights

100 Salesforce, Inc.

San Francisco (CA)

On-site

USD 123,000 - 186,000

Full time

2 days ago
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Job summary

Salesforce is seeking a Data Analytics & Engineering Lead within the Global Partnerships team in San Francisco. You will translate revenue and consumption data into insights that influence executive decisions, and lead the effort to deliver actionable metrics and dashboards.

Ideal candidates combine 6+ years of GTM analytics experience with strong SQL, Tableau, and data storytelling skills, and the ability to collaborate across Finance, Product, and Operations while leveraging AI-assisted

Qualifications

  • 6+ years of experience in GTM, Sales, or Product analytics in SaaS or consulting
  • Strong analytical and strategic thinking skills with experience building models
  • Ability to present to senior leaders with executive-facing decks
  • Experience leading analytics initiatives with cross-functional partners
  • Familiarity with partner ecosystems and AI labs partnerships

Responsibilities

  • Lead analysis of key sales performance and consumption metrics
  • Build executive-ready dashboards and data visualizations
  • Develop strategic recommendations to support decision making
  • Collaborate with Data Engineering and Product to curate data tables
  • Monitor business trends and surface actionable insights

Skills

Analytical thinking
Excel/Tableau
SQL
Data storytelling
Executive communication
Cross-functional collaboration
AI tools

Education

Related degree or equivalent

Tools

Tableau
Snowflake
Claude Code

Job description

Salesforce is seeking a Data Analytics & Engineering Lead within the Global Partnerships team in San Francisco. You will translate revenue and consumption data into insights that influence executive decisions, and lead the effort to deliver actionable metrics and dashboards.

Ideal candidates combine 6+ years of GTM analytics experience with strong SQL, Tableau, and data storytelling skills, and the ability to collaborate across Finance, Product, and Operations while leveraging AI-assisted

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