Director, Data Management Tooling

Salesforce Salesforce · Enterprise · San Francisco, CA +2

Director of Software Engineering to lead Trust & Discovery, a platform team responsible for the discovery, catalog, and governance of trusted data at Salesforce. The role involves leading a team that ships using AI as an operating model, building intelligent systems for governed data accessibility by humans and AI agents, and engaging executive stakeholders on multi-year platform strategy.

What you'd actually do

  1. Lead the metadata and discovery platform — including catalog, auto-classification, stewardship workflows, and cross-platform tag propagation — serving humans and AI agents from a single governed surface.
  2. Own the Trust Center, the consolidated quality and observability layer that surfaces a unified Trust API queryable by both humans and agents across the full data quality stack.
  3. Build the semantic trust layer that gives every governed metric a single canonical definition, accessible in natural language through headless analytics, governed MCPs, and Agentforce — making the compliant path the fastest path for producers and consumers.
  4. Lead a team that ships using AI as an operating model: governed AI-assisted development, self-healing pipelines, and automated evaluation harnesses behind every shipped capability.
  5. Engage CDO and CIO-level stakeholders on multi-year platform strategy and cross-functional alignment with enterprise governance, architecture, and domain engineering teams.

Skills

Required

  • 12+ years of professional engineering experience
  • significant time leading engineering organizations at the Director level or equivalent
  • building data infrastructure at enterprise scale — catalog, governance, quality, observability, or platform tooling
  • leading a team through an AI transformation that changed how the team ships, operates, and measures its own output
  • experience in federated environments where platform and domain teams share accountability
  • Track record of engaging executive stakeholders (CDO, CIO level) on multi-year platform strategy
  • A related technical degree

Nice to have

  • modern data tools: dbt, Snowflake, data observability platforms, or agent infrastructure built on MCP
  • semantic layers, knowledge graphs, or ontology-driven data architectures
  • External contributions — publishing, speaking, or open-source work — on data platform, governance, or AI infrastructure topics

What the JD emphasized

  • AI as an operating model
  • governed data
  • discovery platform
  • semantic trust layer
  • AI agents
  • governance is a property of the platform, not a workflow layered on top of it

Other signals

  • AI as an operating model
  • governed data
  • discovery platform
  • semantic trust layer
  • AI agents