Senior Director, Data Platform - Slack

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Software Engineering

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AI agents — both the ones we ship to customers and the ones our engineers use to build Slack — are fundamentally changing how data gets created, queried, and acted upon. We are seeking a leader who can transform our data engineering stack from a traditional analytics platform into the foundation for agentic analytics (AI agents that autonomously explore, analyze, and surface insights from data) and agentic development (AI-powered engineering tools that use data infrastructure as their backbone).

As Senior Director of Data Engineering, you will lead a ~40-person organization and own the full data engineering stack — from infrastructure and ingestion through to data products, semantic layers, and AI-facing data services. You'll partner closely with Data Science & Analytics as a strategic peer while driving a bold technical vision: making Slack's data platform the best-in-class substrate for both human analysts and AI agents.

This is not a maintenance role. We're looking for someone who sees the agentic future of data platforms and wants to build it.

• Architect the data layers agents rely on — Design and ship data APIs, MCP servers, and semantic interfaces that let AI agents (Slackbot AI, internal coding agents, customer-built Agentforce agents) query, reason over, and act on Slack's data autonomously
• Transform the semantic layer — Evolve our metrics platform from a human-query tool into a machine-readable knowledge that agents can navigate, with governed metric definitions, lineage, and natural-language access patterns
• Build real-time data products — Move beyond batch analytics to streaming data infrastructure that supports sub-second agent decision-making, real-time experimentation, and low-latency retrieval
• Ship agentic analytics tooling — Create the next generation of self-serve analytics where AI agents draft queries, detect anomalies, generate insights, and surface recommendations — replacing manual dashboard-watching with proactive, agent-driven intelligence
• Establish AI-native observability — Instrument the data stack with LLM-aware tracing (Open Telemetry GenAI conventions), token/cost attribution, and quality metrics that treat AI agents as first-class consumers of data infrastructure
• Drive the Data MCP strategy — Own the vision for how Slack's data warehouse, metrics layer, and analytics tools are exposed to AI agents via MCP servers, making Slack's data the most agent-accessible enterprise dataset in the industry

• Own and unify the Data Engineering roadmap across infrastructure, ingestion, data governance, tooling, semantic layer sub-teams
• Serve as the DRI for data engineering, representing data engineering in leadership planning and resolving cross-team priority conflicts
• Partner directly with the Data Science & Analytics organization — establishing and running an effective operating model
• Set data freshness SLAs, warehouse…