Data Analytics Lead

Salesforce•Atlanta, GA

1d•$123,100 - $202,600

About The Position

The Data Analytics & Engineering Lead will work on Salesforce’s Global Partnerships team, which manages alliances with consulting partners, hyperscalers, and AI labs. The role translates complex revenue and consumption data into insights that inform executive decisions and help the organization understand, measure, and grow its business. The position combines analysis, strategic recommendations, reporting, and cross-functional collaboration to drive business impact.

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 is 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 communicating with senior leaders and creating executive-facing decks that convey actionable insight.
Ability to work independently with minimal supervision and deliver high-quality, accurate work in fast-moving environments.
Collaborative approach to cross-team work, including 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 based on 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 with AI tools such as Claude and Code.
Partner with Finance, Product, and Operations to align on success metrics, target setting, and partner telemetry.
Monitor and analyze business trends and performance, proactively surfacing actionable insights.