Senior Director, Data Platform - Slack

Salesforce•Atlanta, GA

2d•$218,400 - $401,400

About The Position

Salesforce is seeking a Senior Director of Data Platform for Slack to transform its data platform from a traditional analytics platform into a foundation for agentic analytics and agentic development. The role leads an approximately 40-person organization and owns the full data stack, from infrastructure and ingestion through data products, semantic layers, and AI-facing data services. The leader partners closely with Data Science & Analytics as a strategic peer and sets the technical vision for a platform serving both human analysts and AI agents. The role will architect data APIs, MCP servers, and semantic interfaces for AI agents; evolve the metrics platform into machine-readable, governed knowledge; build real-time data products and streaming infrastructure; create agent-driven analytics tooling; establish AI-native observability; and own the Data MCP strategy. Operationally, the Senior Director owns and unifies the Data Platform roadmap across infrastructure, ingestion, governance, tooling, and semantic-layer teams. They represent the team in leadership planning, resolve cross-team priority conflicts, establish an effective operating model with Data Science & Analytics, set data freshness, reliability, and cost-optimization standards, and build engineering capacity by hiring, developing, and retaining talent. They also champion the platform’s identity and culture and partner with product, infrastructure, and DevXP leadership.

Requirements

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

Nice To Haves

Experience building data platforms for AI/ML workloads, such as 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, MCP or function calling, and structured versus unstructured data access.
Experience with agentic systems, AI-assisted analytics, or AI-powered developer tools, such as coding assistants, automated data quality, or natural-language-to-SQL.
Track record of shipping data-as-a-product, including APIs, SDKs, or self-serve platforms primarily used by internal or external developers.
Experience operating an embedded pod model pairing engineering with data science or analytics.
Familiarity with modern data stack components, including warehouse infrastructure, streaming ingestion, semantic or metrics layers, governance, OLAP systems, and Airflow-like orchestration.
Experience operating experimentation platforms and A/B testing infrastructure at scale.

Responsibilities

Architect and deliver data APIs, MCP servers, and semantic interfaces that enable AI agents to query, reason over, and act on Slack data.
Transform the metrics platform into machine-readable knowledge with governed metric definitions, lineage, and natural-language access patterns.
Build streaming data infrastructure and real-time products for sub-second agent decisions, experimentation, and low-latency retrieval.
Develop agentic self-serve analytics tools for query drafting, anomaly detection, insight generation, and recommendations.
Establish AI-native observability, including LLM-aware tracing, token and cost attribution, and quality metrics.
Own the strategy for exposing Slack’s warehouse, metrics layer, and analytics tools to AI agents through MCP servers.
Own and unify the Data Platform roadmap across infrastructure, ingestion, governance, tooling, and semantic-layer teams.
Represent Data Platform in leadership planning and resolve cross-team priority conflicts.
Establish and run an effective operating model with Data Science & Analytics.
Set and ensure adherence to data freshness SLAs, warehouse reliability standards, and cost-optimization goals.
Hire, develop, and retain engineering managers and senior individual contributors.
Champion a strong data platform identity and culture.
Partner with product, infrastructure, and DevXP leadership on cross-cutting initiatives.