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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Director, Data Engineering - Slack - **Company:** Salesforce.com, Inc. - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Salary:** $218,400.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Data Analysis, Data as a Services, Information Engineering, Data Governance, Data Infrastructure, Data Warehousing, Programming Tools, Online Analytical Processing, Search Technologies, SQL Databases, Unstructured Data, Working Model 2D, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, AI Coding Agents, Agentic-AI, Data Layers, Data Analytics, Real Time Data, Data Management, Machine Learning Operations, Tools for Reporting, Invoking Functions - **Published:** October 2, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18506021?backUrl=%2Fcareer%2F18506021%2FSenior-Director-Data-Engineering-Slack-Georgia-Atlanta ## About the Role * 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, * 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 ## Description 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 ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow) - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Beyond Autocomplete: Local AI Code Completion Demystified](https://www.wearedevelopers.com/videos/961-beyond-autocomplete-local-ai-code-completion-demystified) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)