Job Description
We are seeking a Salesforce CRM Analytics & AI Specialist to join our team and help transform data into actionable intelligence. In this role, you will leverage Salesforce CRM Analytics (Tableau CRM), Einstein AI, and advanced data modeling techniques to deliver insights that drive smarter business decisions across sales, service, and marketing functions.
You will play a hands-on role in building analytics assets, predictive models, and AI-powered insights, while also acting as a strategic partner to business stakeholders by translating data and AI outputs into meaningful recommendations. This role works closely with Salesforce administrators, developers, data engineers, and business teams to ensure analytics solutions are scalable, trusted, and aligned with business goals.
Responsibilities
Salesforce CRM Analytics & AI Development
Design, develop, and maintain Salesforce CRM Analytics (Tableau CRM) solutions, including dashboards, lenses, datasets, and advanced data visualizations.
Build and optimize Einstein Analytics and AI-driven insights, such as predictive trends, opportunity scoring, forecasting support, and customer behavior analysis.
Implement AI-powered dashboards and stories that surface key KPIs, anomalies, and actionable recommendations.
Data Integration, Modeling & Engineering
Collaborate with business stakeholders to gather analytics and AI requirements and translate them into scalable data models and datasets.
Design and maintain dataflows, recipes, and transformations to support high-quality analytics and AI use cases.
Integrate external and cloud-based data sources into Salesforce using ETL and integration tools to ensure consistency and reliability.
Advanced Analytics, Reporting & Optimization
Build and optimize complex, interactive dashboards for executive, operational, and functional users.
Apply advanced analytics techniques (trend analysis, segmentation, cohort analysis) to uncover insights that support business strategy.
Continuously optimize performance, usability, and scalability of analytics and AI solutions.
AI Strategy & Business Enablement
Partner with business leaders to translate AI and analytics insights into strategic recommendations.
Identify opportunities to leverage Salesforce Einstein features (predictions, discovery, automation, and recommendations) to improve sales performance, customer engagement, and operational efficiency.
Support AI-driven decision-making by explaining model outputs, assumptions, and limitations to non-technical stakeholders.
Data Quality, Governance & Best Practices
Ensure data accuracy, integrity, and reliability through validation rules, monitoring, and ongoing data quality audits.
Follow Salesforce analytics best practices related to security, governance, and performance.
Document analytics architectures, AI use cases, and development standards.
Enablement, Documentation & Continuous Improvement
Create and maintain documentation for analytics solutions, AI models, and workflows.
Provide training, support, and best-practice guidance to end users to increase adoption and data literacy.
Stay current with Salesforce platform enhancements, Einstein AI innovations, and analytics trends, proposing continuous improvements.
Qualifications
Education
Bachelor's degree in Computer Science, Information Technology, Business Analytics, Data Science, or a related field (or equivalent practical experience).
Salesforce & Analytics Experience
Strong hands-on experience with Salesforce CRM Analytics (formerly Tableau CRM / Einstein Analytics).
Experience building dashboards, lenses, datasets, dataflows, and recipes.
Solid understanding of Salesforce data models, objects, and relationships.
Hands-on exposure to Salesforce Einstein AI capabilities, including predictive insights and analytics-driven automation.
AI & Advanced Analytics
Experience applying AI or predictive analytics concepts within Salesforce (e.g., forecasting, scoring, trend prediction, anomaly detection).
Ability to interpret AI outputs and convert them into actionable business insights.
Understanding of responsible AI principles, data bias considerations, and model limitations.
Data Integration & ETL
Experience with ETL and integration tools such as Data Loader, MuleSoft, Talend, Jitterbit, or similar platforms.
Knowledge of Salesforce data import/export, data migration, and integration strategies.
Querying & Data Analysis
Strong proficiency in SOQL and SQL for querying, analysis, and optimization.
Ability to work with large, complex datasets and ensure performant analytics solutions.
Cloud & Platform Knowledge
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP) is a plus.
Experience integrating cloud data sources with Salesforce analytics environments is preferred.
Skills & Competencies
Analytical & AI-Driven Thinking: Strong ability to analyze data and leverage AI insights to solve business problems.
Problem Solving: Proven ability to design analytics and AI solutions for complex use cases.
Communication: Ability to clearly explain analytics findings and AI insights to technical and non-technical audiences.
Collaboration: Strong partnership skills when working with cross-functional teams.
Attention to Detail: High standards for data accuracy, visualization clarity, and solution quality.
Adaptability: Commitment to continuous learning in Salesforce analytics, AI capabilities, and industry best practices.
Time & Priority Management: Ability to manage multiple analytics initiatives with minimal supervision.
Tools & Technologies
Salesforce CRM Analytics (Tableau CRM, Einstein Analytics) Required
Salesforce Einstein AI Required
SOQL & SQL Required
Salesforce Data Loader and data management tools Required
ETL & Integration Tools (MuleSoft, Talend, Jitterbit, SSIS) Preferred
Tableau, Power BI, or similar BI tools Preferred
Cloud Platforms (AWS, Azure, GCP) Preferred
Additional Skills (Optional But Beneficial)
Salesforce Certifications (Administrator, Platform App Builder, CRM Analytics & Einstein Discovery, Data Architecture & Management).
Experience with advanced data visualization and storytelling.
Exposure to AI governance, model monitoring, or analytics enablement programs.
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