Director, Data Management Tooling

Salesforce•San Francisco, CA

4d•$197,300 - $344,700

About The Position

Salesforce is building toward an autonomous future, one where trusted data is the default rather than the extra step, and where the platform itself handles the work humans do today to find, verify, and govern data. With Agentforce built into every layer of our platform, engineers here build the intelligent systems that make governed data accessible to humans and AI agents alike. Data Platform Services (DPS) is the platform team making that future real, and Trust & Discovery is the team at the center of it. We are looking for a Director of Software Engineering to lead Trust & Discovery, the discovery platform, catalog, and governance layer that makes trusted data a property of every data product by design. On the producer side, the compliant path is the fastest path: classification, lineage, ownership, contracts, and semantic definitions are attached at creation, not retrofitted after the fact, so producers move faster with less friction. On the consumer side, human or agent, discovery surfaces the same trusted answer from the same governed source, with confidence and no friction. Trust is not a workflow. It is autonomous. This role reports through DPS leadership to the CDO and CIO. This role has peers across DPS leading the data, quality, and infrastructure platforms, and partners closely with enterprise governance, enterprise architecture, and domain engineering teams whose work intersects this one.

Requirements

12+ years of professional engineering experience, including significant time leading engineering organizations at the Director level or equivalent.
Demonstrated experience building data infrastructure at enterprise scale — catalog, governance, quality, observability, or platform tooling.
Experience leading a team through an AI transformation that changed how the team ships, operates, and measures its own output — not just which tools are on the desktop.
A strong point of view that governance is a property of the platform, not a workflow layered on top of it — with 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 required.

Nice To Haves

Hands-on familiarity with modern data tools: dbt, Snowflake, data observability platforms, or agent infrastructure built on MCP.
Experience with 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.

Responsibilities

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.
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.
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.
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.
Engage CDO and CIO-level stakeholders on multi-year platform strategy and cross-functional alignment with enterprise governance, architecture, and domain engineering teams.