Staff Data Engineer - Slack
California - San Francisco
- Pay
Multiple pay statements — pay source
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.
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- New graduates
- Not stated
- Work authorization
- Not stated
What you’ll work on
Full postingSet architecture and roadmap for the metrics platform, weighing freshness, accuracy, reliability, and cost
Design and scale data models and pipelines that turn billions of records into trusted datasets
Evolve the semantic layer and build APIs and tools for navigating metric definitions and lineage
Lead metric certification, governance, and design reviews
From the employer’s posting
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
Tools in this posting
- Java
- Python
- Scala
- SQL
- dbt
- Iceberg
- Snowflake
- Spark
- Trino
- Airflow
- Go
Source — Tool mentions in context
- 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.
- 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 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.
About Salesforce
Salesforce is the #1 AI CRM, where humans with agents drive customer success together.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 31, 2026 · 4 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on salesforce.wd12.myworkdayjobs.com. The employer’s form will show what is required.
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Job description
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 EngineeringJob 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.
Accommodations
If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.
Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.
Posting Statement
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
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.Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
This passage needs a closer read in the full description.
- Location & working pattern
California - San Francisco
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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