Data Analytics Lead

Salesforce•San Francisco, CA

About The Position

The Data Analytics & Engineering Lead on Salesforce’s Global Partnerships team helps the organization understand, measure, and grow its business by translating revenue and consumption data into insights that inform executive decisions. The role combines analytical work with ownership of initiatives through to measurable impact. It involves analyzing sales performance and consumption, building executive-ready dashboards, developing recommendations, and collaborating with teams to improve data and reporting infrastructure.

Requirements

At least 6 years of experience building and interpreting complex datasets in a GTM, Sales, or Product analytics context at a consulting firm or high-growth SaaS company; B2B experience preferred.
Strong analytical and strategic thinking skills, with demonstrated experience building models and analyzing complex datasets using Excel and/or Tableau.
Ability to lead through ambiguity, prioritize effectively, cut through noise, and execute with limited information.
Exceptional written, verbal, and presentation skills, including experience communicating with senior leaders and creating executive-facing decks that convey actionable insights.
Ability to work independently with minimal supervision and deliver high-quality, accurate work in fast-moving environments.
Collaborative approach to working across teams, building trust, taking ownership, and bringing others along.

Nice To Haves

SQL proficiency for data querying and exploration.
Experience with Tableau, Snowflake, Claude Code, and/or similar AI-assisted coding tools to accelerate analysis.
Familiarity with partner ecosystems, Hyperscaler GTM motions, or AI labs partnerships.
Prior experience supporting C-suite or VP-level business reviews.
Related degree or equivalent relevant experience.

Responsibilities

Lead analysis and discovery of sales performance and consumption metrics, including pipeline, bookings, and growth indicators.
Build and maintain executive-ready dashboards and data visualizations that provide revenue and consumption insights to leadership.
Develop strategic recommendations from quantitative and qualitative analysis to support high-stakes decisions.
Collaborate with Data Engineering and Product to curate data tables and evolve reporting infrastructure, accelerating time to insight using AI tools such as Claude and Code.
Partner with Finance, Product, and Operations to align on success metrics, target setting, and partner telemetry.
Monitor business trends and performance on an ongoing basis and proactively surface actionable insights.