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About the Role
The Metrics Foundations team sits within Slack's Data Engineering organization, building trusted datasets and metrics that power decisions across Product, Analytics, Marketing, Sales, and Operations. This role sets the technical direction for how Slack defines, computes, governs, and serves its most critical metrics, serving 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.
Responsibilities
- 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.
Requirements
- 10+ years of software or data engineering experience, including 6+ years hands-on with data architecture, data modeling, and metadata management.
- Led complex, multi-team technical initiatives as an individual contributor and drive alignment across Engineering, Product, Data Science, and Analytics without formal authority.
- 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.
- Hands-on experience with Spark, Trino, Airflow, Iceberg, and Snowflake, and with dimensional and star/snowflake modeling.
Skills
- Data architecture
- Data modeling
- Metadata management
- SQL
- Python
- Go
- Java
- Scala
- Spark
- Trino
- Airflow
- Iceberg
- Snowflake
- Dimensional modeling
- Star modeling
- Snowflake modeling
- Infrastructure for AI agents
- Model Context Protocol (MCP) servers
- Tool-use APIs
- Evaluation harnesses
- Semantic layers
- Metrics platforms
- Data catalogs
- Lineage tools
- dbt
- sqlmesh
- Datahub
- Cube
- LookML
- Experimentation platforms
- Metrics
- Exposure logging
- Guardrails for A/B testing
Location
- Select cities within the San Francisco and New York City metropolitan area
Work Type
- Full-time
Experience Level
- Staff Data Engineer
- 10+ years of software or data engineering experience
- 6+ years hands-on with data architecture, data modeling, and metadata management
Education Level
- A related technical degree required.
Salary/Compensations
- 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.
Benefits
- Time off programs
- Medical
- Dental
- Vision
- Mental health support
- Paid parental leave
- Life and disability insurance
- 401(k)
- Employee stock purchasing program
About the Company
- Salesforce is the #1 AI CRM, where humans with agents drive customer success together.
- 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.
- Agentforce is the future of AI, and you are the future of Salesforce.
Equal Opportunity
- Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment.
- We believe in equality for all.
- 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.
- 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.