Staff Data Engineer - 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.

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.
• You have deep SQL expertise, strong Python skills, and working proficiency in Go, Java, or Scala, with a record of architecting scalable, cost-efficient data models and pipelines.
• You have hands-on experience with Spark, Trino, Airflow, Iceberg, and Snowflake, and with dimensional and star/snowflake modeling.
• A related technical degree required.

Even Better If...

• You have experience building infrastructure or tools for AI agents, such as Model Context Protocol (MCP) servers, tool-use APIs, or evaluation harnesses.
• You have experience with semantic layers, metrics platforms, data catalogs, or lineage tools such as dbt, sqlmesh, Datahub, Cube, or LookML.
• You have experience with experimentation platforms, including metrics, exposure logging, and guardrails for A/B testing.
• You prototype early, balance speed with judgment, and measure your impact by what the teams around you ship.

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.

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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 $197,300 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $237,700 - $344,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.