Staff Data Engineer - Slack

About the role

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

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.

The Experience

The Metrics Foundations team sits within Slack's Data Engineering organization in Data & Insights, building the trusted datasets and metrics that power decisions across Product, Analytics, Marketing, Sales, and Operations. The team partners with Product, Data Science, Analytics, and Engineering to define and govern metrics with consistent quality and clear service level agreements (SLAs).

Increasingly, AI agents and developer tools consume these metrics alongside people, so you build the trusted, machine-readable foundation that maps business questions to the right metric definitions and tables. As a Staff Data Engineer, you set the technical direction for how Slack defines, computes, governs, and serves its most critical metrics, and you serve as the technical lead for Agentic Analytics on the metrics side.

This is a senior individual contributor role with organization-wide scope and multi-quarter impact.

What You'll Actually Be Doing

- Set the architecture and roadmap for the metrics platform, from ingestion and canonical datasets to the semantic layer and serving, making clear tradeoffs between freshness, accuracy, reliability, and cost.

- Design and scale data models and pipelines that turn billions of records into trusted datasets with measurable quality, predictable SLAs, and freshness signals for consumers.

- Evolve the semantic layer and build the APIs and tools that let people and AI agents navigate metric definitions, lineage, and ownership, and draft accurate queries.

- Lead metric certification, governance, and design reviews, and mentor senior engineers, using AI-assisted development to deliver faster without compromising quality.

You're Our Person If...

- You have 10+ years of software or data engineering experience, including 6+ years hands-on with data architecture, data modeling, and metadata management.

- You have led complex, multi-team technical initiatives as an individual contributor and drive alignment across Engineering, Product, Data Science, and Analytics without formal authority.