About the Role
This role turns Salesforce data into decisions. The Salesforce Analytics Developer designs, builds, and supports reporting and analytics assets natively inside the Salesforce platform — CRM Analytics dashboards and datasets, native reports and report types, Einstein predictions, and the data model changes that make them accurate. \n\nIt is a builder role, not platform administration or warehouse engineering. The incumbent works directly from business questions posed by Sales, Revenue Operations, Finance, and Operations leaders, and owns the correctness, performance, security, and adoption of what they publish. Where Salesforce data feeds the enterprise data platform and downstream BI, this role is the authoritative source of Salesforce-side metric definitions and data quality, and partners with — but does not own — the pipeline and warehouse layers.
Responsibilities
• Analytics development — approx. 50% • Build and maintain CRM Analytics (formerly Tableau CRM) dashboards, lenses, datasets, and recipes, including dataflow design, dataset registration, and refresh scheduling. • Develop and optimize Salesforce native reports, custom report types, and dynamic dashboards for operational and executive audiences. • Write and tune SOQL and SAQL; use bindings, filters, and faceting to build interactive, drill-through analytics. • Configure and validate Einstein Discovery / Prediction Builder models where predictive scoring adds measurable value, including refresh monitoring. • Implement formula fields, roll-up summaries, and supporting schema changes so reporting is accurate at the source rather than patched downstream. • Requirements and data quality — approx. 25% • Elicit requirements directly from business stakeholders, define metrics precisely, and challenge requests that would produce misleading results. • Document metric definitions, calculation logic, data lineage, and refresh cadence for every published asset. • Identify and remediate Salesforce data quality issues affecting reporting — duplicates, inconsistent stage or classification values, ownership and territory gaps — and escalate systemic issues to data governance. • Reconcile Salesforce-sourced metrics against finance and operational systems of record and investigate variances to root cause. • Governance, security, and release management — approx. 15% • Implement row-level and field-level security consistent with the Salesforce sharing model, so dashboards never expose data a user could not see in the underlying records. • Apply data classification and handling requirements to reporting assets, including customer-segment and jurisdictional restrictions. • Manage changes through source control and the standard sandbox-to-production release process, with documented testing and rollback. • Maintain an analytics asset inventory; review usage and retire assets that are unused, duplicative, or superseded. • Enablement and support — approx. 10% • Provide tier-2/3 support for reporting defects, dataflow failures, and dashboard performance issues within agreed service levels. • Train business users on self-service reporting and publish short guidance for recurring questions. • Evaluate each Salesforce seasonal release for analytics-affecting changes and regression-test critical dashboards.
Must Have
• Three to five years building reporting and analytics on the Salesforce platform, including at least two years with CRM Analytics / Tableau CRM (dataflows or recipes, datasets, dashboards, bindings). • Proficiency with Salesforce native reporting: custom report types, cross-filters, bucket fields, summary formulas, dashboard filters. • Working knowledge of the Salesforce data model and sharing and visibility model (org-wide defaults, role hierarchy, sharing rules, field-level security) and how each affects reporting results. • Proficiency with SOQL and SQL; working proficiency with SAQL or a comparable analytics query language; dimensional data modeling fundamentals (facts, dimensions, grain). • Gathers requirements directly from business stakeholders without an intermediary analyst, and can explain a metric definition or variance to a non-technical executive audience. • Experience working in a change-controlled environment with sandboxes, documented testing, and scheduled releases. • Bachelor's degree in information systems, computer science, analytics, business, or a related field or equivalent practical experience.
Nice to Have
• Salesforce CPQ, Revenue Cloud, or quote-to-cash data structures and the reporting challenges they create. • Feeding Salesforce data into an enterprise data platform or lakehouse and reconciling native reporting against downstream BI, for example Power BI semantic models. • Replication and integration tooling — Fivetran, Boomi, Salesforce Bulk/Streaming APIs; entity resolution and customer master data. • Apex, Lightning Web Components, or Flow sufficient to build supporting automation and custom analytics components. • Multi-country orgs (multi-currency, multi-language, jurisdictional data handling) and regulated environments with formal classification and access reviews. • Git and Salesforce DevOps tooling (Salesforce DX, Gearset, Copado); Tableau Cloud/Server or Tableau Next alongside CRM Analytics. • Preferred Certification — Salesforce Certified CRM Analytics and Einstein Discovery Consultant; Salesforce Certified Platform Administrator (formerly Salesforce Certified Administrator). • Also valued Certification — Platform App Builder; Tableau Data Analyst; Data 360 Consultant (formerly Data Cloud Consultant); Business Analyst.