Director, Software Engineering

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.

Your Impact

• Define and execute the technical roadmap for scalable, high-performance distributed compute systems leveraging Spark, Flink, and Ray.
• Direct the architecture and design of data processing frameworks that power mission-critical batch, streaming, and AI inference workloads in Salesforce Data Cloud.
• Lead a team of engineers, fostering a culture of technical excellence, mentorship, and accountability for end-to-end delivery, performance, and scalability of the Compute Platform services.
• Collaborate strategically with product management, architecture, and cross-functional engineering teams to align on priorities and deliver key functionalities.
• Drive innovation in areas such as real-time data streaming, low-latency processing, vectorized computation, and cost efficiency.
• Champion reliability, cost governance, and advanced observability for distributed data workloads running on Kubernetes (EKS) at petabyte scale.
• Influence the broader Data Cloud organization on best practices for distributed systems and data engineering.

What You'll Bring

• 12+ years of progressive experience in software engineering, with a minimum of 5+ years managing and leading high-performing distributed systems or Big Data engineering teams.
• Deep executive-level expertise in architecting, performance tuning, and operating large-scale distributed data systems and compute frameworks like Apache Spark, Flink, or Ray in production.
• Exceptional programming skills in Java, Scala, or Python.
• Comprehensive understanding of distributed computing concepts (task scheduling, checkpointing, fault tolerance, state management) and their strategic application.
• Proven experience deploying, optimizing, and governing big data workloads on modern container platforms, specifically Kubernetes (EKS).
• Hands-on experience with data formats (Parquet, ORC, Delta) and advanced streaming frameworks.
• Demonstrated ability to make complex trade-offs involving scale, cost, reliability, and time-to-market.
• Familiarity with modern observability and DevOps tools (Prometheus, Grafana, OpenTelemetry).
• Strong communication, collaboration, and executive presence with a track record of attracting, developing, and retaining top engineering talent.
• A related technical degree required.