Senior Director, Data Engineering - Slack

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Job Category

Software Engineering

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

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.

What You'll Build (Transform)

• 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 (OpenTelemetry 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

What You'll Run (Operate)

• 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 reliability, and cost optimization standards across ingestion and infrastructure teams and ensure the data platform meets those standards and goals
• Build and scale engineering capacity — hire, develop and retain top EM and senior IC talents
• Champion a strong data engineering identity and culture
• Partner with product, infrastructure, and DevXP leadership on cross-cutting initiatives

Minimum Qualifications

• 10+ years of experience in data engineering, data platform, or infrastructure engineering roles, including 5+ years in engineering leadership at the Director level or above
• Proven track record building and scaling data platforms (ingestion pipelines, warehousing, semantic/metrics layers) at consumer or enterprise SaaS scale
• Experience leading through organizational change — team consolidations, re-orgs, or multi-team integrations
• Demonstrated success partnering with Data Science / Analytics leadership as a peer stakeholder
• Strong track record of hiring, developing, and retaining engineering managers and senior ICs
• Excellent cross-functional communication skills, with experience presenting technical vision and strategy to executive stakeholders
• A related technical degree required

Preferred Qualifications

• Experience building data platforms that serve AI/ML workloads — not just dashboards and reports, but data infrastructure optimized for model training, feature serving, RAG retrieval, or agent-driven queries
• Hands-on understanding of how LLMs and AI agents consume data — including semantic layers, embeddings, vector search, tool-use patterns (MCP, function calling), and structured vs. unstructured data access
• Experience with agentic systems, AI-assisted analytics, or building developer tools powered by AI (e.g., AI coding assistants, automated data quality, natural-language-to-SQL)
• Track record shipping data-as-a-product — APIs, SDKs, or self-serve platforms where internal or external developers are the primary consumers
• Experience operating a "pod" or embedded working model that pairs engineering with data science/analytics
• Familiarity with modern data stack components: warehouse infrastructure, streaming ingestion, semantic/metrics layers (governance, OLAP systems, Airflow-like orchestration)
• Experience running experimentation platforms and A/B testing infrastructure at scale

Unleash Your Potential

When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.

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Posting Statement

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In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $218,400 - $365,200 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $263,200 - $401,400 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.