Digital Success Analytics Engineer

Role Overview

The Digital Success Analytics team powers decisions for Digital customer experience success at Salesforce. We are becoming a truly data-driven enterprise. That means trusted, governed metrics, world-class self-serve analytics, and AI-ready insights that Customer Success teams use every day.

What You Will Do

Deliver decision-grade insights, measure and compare product performance, build predictive and statistical solutions, define metrics and the ‘North Star’, champion a single source of truth for metrics, build dashboards and data stories, enable self-serve and AI-augmented analytics, data instrumentation and measurement strategy, data governance and responsible AI, partner and influence, operate with rigor.

Why It Might Be a Fit

You will be working with a team that is passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce’s core values at the heart of it all. You will have the opportunity to work on a wide range of projects, from building predictive models to creating data visualizations, and will be working with a team that is committed to delivering high-quality results.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, AI, Information Technology, or a related field.
• 7-8 years of experience in analytics, as a Data Analyst, Analytics Engineer, Data Scientist, or BI Engineer.
• Management consulting experience (a plus): Experience at a consulting firm, or in an internal strategy or consulting function, structuring ambiguous problems and turning findings into executive-ready recommendations.
• Advanced SQL (Snowflake) and Python for analysis, modeling, and automation.
• Strong statistical foundation, including probability distributions, hypothesis testing, confidence intervals, p-values, and experiment design.
• Experience building predictive or ML models (regression, classification, clustering, time series, anomaly detection).
• Proficiency in Tableau and other BI tools.
• Familiarity with the Salesforce ecosystem.
• Git and basic CI/CD for reproducible, production-ready analytics.
• Working knowledge of data modeling concepts (pipelines, medallion architecture).

Benefits

• Time off programs
• Medical
• Dental
• Vision
• Mental health support
• Paid parental leave
• Life and disability insurance
• 401(k)
• Employee stock purchasing program