Data Analytics and AI Solutions Lead

Salesforce
India - HyderabadPosted 14 April 2026

Job Description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Software Engineering Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Role Overview : The Cloud Success Data Intelligence team operates within the Salesforce Customer Success Group. This team is dedicated to harnessing data-driven insights regarding customer usage, engagement, technical satisfaction scores and other industry-standard Key Performance Indicators (KPIs). These valuable insights empower customers to leverage the world's premier CRM platform, while leaders in the Customer Success Group use this intelligence to drive process enhancements for an improved customer experience. Data engineering forms the foundation of the Cloud Success Data Intelligence team's operations, enabling the acquisition, maintenance and automation of data to generate actionable insights. We are looking for a Senior Data Analytics with strong AI tool expertise who can combine data engineering, advanced analytics and AI-driven problem solving to accelerate data-led decision making. The ideal candidate will actively leverage modern AI tools, automation platforms and intelligent analytics solutions to improve productivity, insight generation and business outcomes. You will serve as a Data & AI enabler for the organization, helping teams operationalize data and adopt AI capabilities responsibly and effectively. Key Responsibilities Drive adoption of AI-powered tools, copilots and automation platforms to enhance data engineering, analytics and reporting workflows. Design and build scalable data pipelines, curated datasets and data models optimized for analytics, AI and Machine Learning consumption. Create intuitive dashboards, executive visualizations and self-service analytics solutions that improve data accessibility and storytelling. Deliver data analytics-driven insights by leading end-to-end projects from data discovery and modeling through to actionable recommendations for business stakeholders. Evaluate emerging AI and data technologies , recommending solutions that improve productivity, scalability and analytics acceleration. Ensure data quality, governance, reliability and responsible AI practices , supporting both batch and near real-time data processing environments. Act as a trusted advisor to business and leadership stakeholders on Data & AI opportunities. Drive cross-functional collaboration across Analytics and Operations teams. Required Qualifications 8 years of experience in Data Engineering/Data Analytics roles. Demonstrated hands-on experience using AI tools, Generative AI platforms or AI-assisted development environments . Strong expertise in SQL and Python (or equivalent programming language). Experience with modern cloud data platforms (Databricks, Snowflake, BigQuery, Redshift, etc.). Proven ability to translate complex data into clear insights through visualization and storytelling. Strong analytical reasoning, business problem-solving and stakeholder engagement skills. Excellent communication and executive presentation capabilities. Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do ... (truncated, view full listing at source)
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