Salesforce Behavioral Interview Template — Engineering Data Analyst (Customer 360, Tableau/CRM Analytics)

This behavioral interview at Salesforce evaluates how an Engineering Data Analyst operates within Salesforce’s values-driven culture (Trust, Customer Success, Innovation, Equality, Sustainability) and its Customer 360 ecosystem. Expect scenario-based, STAR-format deep dives that probe: (1) Values alignment and decision-making—how you prioritized work using goal frameworks like V2MOM, handled tradeoffs under ambiguity, and upheld trust when dealing with sensitive customer data; (2) Stakeholder management across GTM and product teams—partnering with Sales Ops, Customer Success, Marketing, and Product/Engineering to clarify ambiguous executive asks, turn them into precise metrics/KPIs (e.g., ARR/ACV, churn/retention, NPS/CSAT, adoption), and influence without authority; (3) Data storytelling for impact—structuring narratives around insights, building executive-ready dashboards in Tableau or CRM Analytics, and tying analyses to business outcomes (pipeline health, renewal risk, campaign performance); (4) Data governance & ethics—ensuring privacy, security, and compliance while maintaining data quality, lineage, and reproducibility; (5) Analytical rigor & experimentation—defining success criteria, running/assessing A/B tests, addressing bias and confounders, and quantifying impact; (6) Collaboration in a Slack-first environment—async communication, documentation, and cross-time-zone teamwork; (7) Learning mindset—using Trailhead or similar to upskill, mentoring others, and reflecting on feedback. Format typically includes rapport-building, 2–3 story deep dives with iterative probing, and time for your questions targeted at customer impact and cross-cloud collaboration.