Principal Data Engineer

Salesforce•San Francisco, CA

7d•Hybrid

About The Position

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. Data Solutions is the force that propels Salesforce into the AI era, informing—through trusted data and artificial intelligence—the path forward to be smarter in every dimension. Delivering everything from financial forecasting and customer health to adoption insights and curated data, Data Solutions serves as the unbiased partner to every data trailblazer across Salesforce. As part of this organization, Cloud Analytics operates as the strategic product analytics engine, partnering directly with cloud leadership to drive high-stakes decision-making through rigorous metrics and insights. Sitting within Cloud Analytics as a forward-deployed partner to the AgentExchange and Partner Ecosystem business, this role collaborates hand-in-hand with product, engineering, and data leadership to co-build the foundations, core metrics, strategic insights, and autonomous agents driving the product forward. As a Principal Data Engineer for AgentExchange, you will serve as the chief data architect and technical authority powering our next-generation product analytics and AI platform. In this high-leverage position, you will design, scale, and maintain the enterprise-grade data infrastructure, real-time pipelines, and feature stores that feed both high-stakes decision systems and autonomous AI agents. Operating on the front lines alongside decision scientists, software engineers, and product leaders, you will transform high-volume data streams into pristine, reliable, and high-performing technical foundations.

Requirements

7+ years of hands-on data engineering experience building complex, enterprise-scale data platforms, distributed systems, and real-time data pipelines. Must have a track record of actively shipping production code alongside architectural leadership.
Mastery of modern distributed computing, data lakehouse architectures, and cloud data warehouses, alongside deep expertise in orchestration tools (e.g., Airflow, Dagster).
Demonstrated experience engineering data systems for LLMs, agentic workflows, feature stores, or vector retrieval pipelines. You build the data plumbing that makes AI systems fast, accurate, and scalable.
Expert proficiency in Python, Scala, or Java, alongside expert-level SQL tuning and deep familiarity with software engineering best practices (Docker, Git, CI/CD, IaC).
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical discipline (or equivalent practical impact).
Strong communication skills with a proven track record of distilling complex system architecture decisions into clear business trade-offs for technical and non-technical executives alike.

Responsibilities

Architect, build, and scale the foundational data platforms, lakehouses, and high-throughput pipelines that power AgentExchange product analytics, metrics, and agentic workflows.
Design and deploy production-grade data pipelines, feature stores, and event-driven architectures that enable autonomous AI agents to operate reliably at enterprise scale.
Establish end-to-end data governance, quality frameworks, lineage tracking, and performance monitoring to ensure zero-downtime reliability for mission-critical data assets.
Serve as the principal technical authority on data architecture, partnering seamlessly with decision scientists, software engineers, and product managers to translate complex business needs into elegant technical systems.
Co-own the long-term data technology roadmap for AgentExchange, anticipating scale bottlenecks and driving architectural evolution ahead of product growth.
Elevate the engineering bar across Cloud Analytics by establishing standards for code quality, testing, CI/CD, and system design, while mentoring engineers across the broader organization.