Director, Data Engineering — Customer Success Score

Salesforce Salesforce · Enterprise · San Francisco, CA +1

Director of Data Engineering responsible for the strategic direction, architectural vision, and execution of data systems for Customer Success Score (CSS), a critical product intelligence asset at Salesforce. The role involves leading multiple engineering teams, setting technical standards for distributed data systems, and influencing AI-first product strategy. Focus is on building data products that power agentic intelligence and self-optimizing product experiences at enterprise scale.

What you'd actually do

  1. Own the roadmap for the CSS data platform, aligning engineering investment with Salesforce's agentic and AI-first product strategy
  2. Establish architectural principles and governance standards for telemetry, semantic modeling, and metadata-driven discovery at enterprise scale
  3. Drive convergence across product analytics, ML infrastructure, and AI data foundations — breaking down silos and creating shared organizational leverage
  4. Set and uphold the technical bar for distributed data systems — including fault-tolerant batch and streaming architectures (Spark, Trino, Flink, Kafka, dbt, Snowflake)
  5. Lead and grow multiple engineering teams, including managers and senior individual contributors

Skills

Required

  • 15+ years of experience in data or platform engineering
  • 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

Nice to have

  • Experience with AI data engineering patterns, agentic data systems, or autonomous pipeline design
  • Familiarity with MCP, knowledge graphs, or modern metadata platforms
  • Experience designing programmatic data discovery and consumption frameworks

What the JD emphasized

  • AI-first product strategy
  • agentic intelligence
  • autonomous agent reasoning
  • AI-native product experiences
  • enterprise scale

Other signals

  • AI-first product strategy
  • agentic intelligence
  • data systems behind Customer Success Score
  • enterprise scale
  • autonomous agent reasoning
  • AI-native product experiences