Senior Data Engineer

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. Senior Data Engineer, Customer Success Data Platform About Salesforce We’re Salesforce, the Customer Company, inspiring the future of business with AI Data CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too — driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good – you’ve come to the right place. Position Overview: As a Data Engineer at Salesforce within the Data & Analytics organization, you will collaborate with cross-functional teams to create and manage robust data solutions that support our analytics and business intelligence initiatives, building scalable and efficient data pipelines, optimizing data workflows, and ensuring data quality and reliability. The Customer Success Data Platform organization sits at the intersection of Automation, Analytics, and AI, pushing the boundaries of Salesforce technology as Customer 0 and providing trusted data that supports the AI Human tandem. What You’ll Do Implement Retrieval Systems : Design and implement robust search indices that enable AI agents to perform complex retrievals across the Salesforce data ecosystem. Infrastructure for Inference: Partner with Decision Scientists to build the specialized infrastructure required for attribution and causal modeling. Customer Graphs and Identity: Build on top of identity graphs, overlaying structured, unstructured, and real-time insights for powering Agentic systems and human-facing applications. Data Architecture and Development: Help modernize the data architecture and catalog for AI consumption and Human augmentation, leading with precision, rigor, and scale. Activate Trusted Metrics at Scale: Turn data and insights into action through proactive automation, and reactive interactions. Operational Excellence : Establish and enforce rigorous technical standards for data quality, latency, and index freshness to ensure agents provide reliable, real-time insights. Cross-Functional Collaboration : Partner with Decision Scientists, Data Scientists, Product Managers, and Engineering Leaders to translate complex business needs into scalable, production-ready technical solutions. AI Integration & Automation : Lead high-impact efforts to automate the data delivery pipeline, ensuring seamless integration between internal databases, third-party APIs, and the AI orchestration layer. Qualifications: 6 years of experience as a Data Engineer or in a similar role. Proficiency in data engineering tools and languages, such as Python, SQL, and Spark. Strong understanding of database concepts, data modeling, and ETL processes with tools like Airflow, dbt, Informatica, etc. Experience with cloud-based data solutions (e.g., AWS, Azure, Google Cloud). Familiarity with data warehousing, SQL, NoSQL databases, and data integration techniques. Experience with the Salesforce Ecosystem, specifically Data Cloud. Problem-solving skills to troubleshoot ... (truncated, view full listing at source)