Director, Data Engineering — Customer Success Score

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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.

About the Role

We're building data products that will define Salesforce's next era of agentic intelligence — powering smarter, adaptive, and self-optimizing product experiences at enterprise scale. As Director of Data Engineering, you'll set the strategic direction, architectural vision, and organizational execution for the data systems behind Customer Success Score (CSS), one of Salesforce's most critical product intelligence assets. This is a high-visibility leadership role for a strategic technologist who thrives at the intersection of data, AI, and platform engineering.
 

What You'll Do

Platform Strategy & Roadmap

• Own the roadmap for the CSS data platform, aligning engineering investment with Salesforce's agentic and AI-first product strategy

• Establish architectural principles and governance standards for telemetry, semantic modeling, and metadata-driven discovery at enterprise scale

• Drive convergence across product analytics, ML infrastructure, and AI data foundations — breaking down silos and creating shared organizational leverage

• Represent data engineering at the executive level; shape organizational priorities and secure resources for strategic initiatives

Technical Architecture & Excellence

• Set and uphold the technical bar for distributed data systems — including fault-tolerant batch and streaming architectures (Spark, Trino, Flink, Kafka, dbt, Snowflake)

• Define engineering standards across software quality, CI/CD, observability, and reliability

• Guide platform evolution to support autonomous agent reasoning, real-time adaptive decisioning, and AI-native product experiences

• Champion semantic consistency, metric governance, and trusted signal definition across the organization

• Evaluate emerging technologies and drive adoption decisions that extend the platform's strategic value

Organizational Leadership & Talent

• Lead and grow multiple engineering teams, including managers and senior individual contributors

• Build a culture of ownership, psychological safety, and high accountability

• Drive succession planning, leadership development, and talent retention

• Define hiring strategy and org structure to scale with business needs

Executive Influence & Cross-Functional Partnership

• Build deep partnerships with product, data science, AI platform, telemetry engineering, and infrastructure leaders

• Communicate architecture, trade-offs, and investment decisions clearly to VP and C-suite stakeholders

• Align technical execution with business outcomes and enterprise priorities

• Influence Salesforce-wide standards for data and AI engineering beyond your direct scope

What We're Looking For

Required Qualifications

• 15+ years of experience in data or platform engineering, with 5+ years leading engineering managers and multi-team organizations

• Proven track record building and scaling high-performing engineering orgs in complex, cross-functional environments

• Deep expertise with Spark, Trino/Presto, dbt, Snowflake, and modern lakehouse architectures

• Experience with streaming systems (Flink, Kafka), including topic design, partitioning, and scaling

• Strong command of semantic layers, data modeling, and enterprise metrics systems

• Experience with AWS cloud infrastructure (S3, EMR, ECS, IAM) and containerized environments

• Executive-level communication skills — able to influence without authority and present at the VP/C-suite level

• A related technical degree required.

Preferred Qualifications

• Experience with AI data engineering patterns, agentic data