Salesforce

Principal Data Engineer

$197,300 - $313,700 annuallyFull-time · California - San Francisco
✓ Verified live on the employer's own system · added 5 days ago
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Senior · 7+ yrs exp

Requirements

Education: Bachelor's degree or related field

Experience: 7+ years

Skills & tools

SalesforceMachine LearningFinancial AnalysisData AnalysisTeam LeadershipDevopsDistributed SystemsPlumbing
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Full job description

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.

- Data Architecture & Strategy: Architect, build, and scale the foundational data platforms, lakehouses, and high-throughput pipelines that power AgentExchange product analytics, metrics, and agentic workflows.

- Agentic Infrastructure & Orchestration: Design and deploy production-grade data pipelines, feature stores, and event-driven architectures that enable autonomous AI agents to operate reliably at enterprise scale.

- Platform Excellence & Reliability: Establish end-to-end data governance, quality frameworks, lineage tracking, and performance monitoring to ensure zero-downtime reliability for mission-critical data assets.

- Cross-Functional Engineering Leadership: 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.

- Technical Roadmap Ownership: Co-own the long-term data technology roadmap for AgentExchange, anticipating scale bottlenecks and driving architectural evolution ahead of product growth.

- Mentorship & Engineering Rigor: 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.

- Proven Experience: 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.

- Systems Architecture & Data Engineering: Mastery of modern distributed computing, data lakehouse architectures, and cloud data warehouses, alongside deep expertise in orchestration tools (e.g., Airflow, Dagster).

- AI & Agentic Infrastructure: 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.

- Software Engineering Mastery: 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).

- Technical Foundation: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical discipline (or equivalent practical impact).

- Architectural Influence: 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.

The typical base salary range for this position is $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually.

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