As the Senior Director of Data Engineering at Salesforce, you will lead a team of approximately 40 professionals to transform the data engineering stack into a foundation for agentic analytics and development. This role focuses on architecting data layers that AI agents rely on, evolving the semantic layer, and building real-time data products. You will partner closely with Data Science & Analytics to drive a bold technical vision and ensure that Slack's data platform is optimized for both human analysts and AI agents. This position requires a strong leader who is passionate about innovation and the future of data platforms.

• 10+ years of experience in data engineering, data platform, or infrastructure engineering roles.
• 5+ years of engineering leadership experience at the Director level or above.
• Proven track record of building and scaling data platforms at consumer or enterprise SaaS scale.
• Experience leading through organizational change such as team consolidations or multi-team integrations.
• Demonstrated success partnering with Data Science and Analytics leadership as a peer stakeholder.
• Strong track record of hiring, developing, and retaining engineering managers and senior individual contributors.
• Excellent cross-functional communication skills with experience presenting technical vision and strategy to executive stakeholders.
• A related technical degree is required.

• Architect the data layers that agents rely on by designing and shipping data APIs and semantic interfaces.
• Transform the semantic layer to evolve the metrics platform into a machine-readable knowledge base.
• Build real-time data products to support sub-second agent decision-making and low-latency retrieval.
• Ship agentic analytics tooling to create self-serve analytics where AI agents generate insights and surface recommendations.
• Establish AI-native observability by instrumenting the data stack with LLM-aware tracing and quality metrics.
• Drive the Data MCP strategy to make Slack's data the most agent-accessible enterprise dataset in the industry.
• Own and unify the Data Engineering roadmap across various sub-teams.
• Serve as the Directly Responsible Individual for data engineering in leadership planning.
• Partner directly with the Data Science and Analytics organization to establish an effective operating model.
• Set data freshness SLAs and ensure the data platform meets reliability and cost optimization standards.
• Build and scale engineering capacity by hiring and developing top talent.
• Champion a strong data engineering identity and culture within the organization.

• Employees at Slack, as part of Salesforce, are often offered comprehensive benefits focused on wellbeing and inclusion, including competitive health-care coverage, time off to rest, recharge and volunteer, and holistic programs that support mental health, family planning and overall work–life balance.