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Salesforce

Staff & Senior Staff Software Engineer, Data Platform - Slack

  • Office
  • 6+ years

Salary

Not stated

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 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

Agents are changing how people build software and analyze data. Slack’s data platform needs to support both agents that surface insights, and developer tools that use data to provide quantitative feedback in the product iteration process.

We’re looking for a Staff or Senior Staff engineer to help build out Agentic Analytics at Slack. You’ll collaborate on technical direction, build, and go from early prototypes through production. Your work could span many parts of the data stack: ingestion, infrastructure, semantic layers, and the interfaces that make data useful to humans and AI agents.

You’ll partner with engineers across Data Engineering, Data Science, product, core infrastructure, and developer experience to quickly iterate on high leverage problem spaces and ship pragmatic solutions.

What You'll Actually Be Doing

Build data platform for agents. Design APIs, MCPs, and tools that let agents map data concepts to the right entities in the data warehouse.

Make data digestible. Improve our semantic layer so people and agents alike can navigate metric definitions, lineage, ownership, and reliability.

Make data on time (or provide signal when it’s not). Build ingestion and infrastructure for timely analytics, and experimentation. Evaluate tradeoffs between freshness, accuracy, reliability, and cost.

Ship tools that make data easy to analyze. Make it easy to draft accurate queries, do root cause analysis, and build visualizations.

Own the path to production. Drive architecture, implementation, rollout, and adoption.

Raise the engineering bar across teams by helping engineers make good design decisions, resolve technical dependencies, and grow through mentorship and leading by example.

You're Our Person If...

8+ years of experience building and operating a data platform

A track record of leading complex technical projects across teams as an individual contributor

Strong software engineering skills balanced with deep data expertise

Clear technical communication and the ability to build alignment with engineers, data scientists, analysts, and product partners

Strong proficiency in programming languages like Python, Go, Java, or similar

Even Better If...

Experience building infrastructure or tools for AI agents

Experience with semantic layers, metrics platforms, data catalogs, or lineage. These might include familiarity with tools like Airflow, dbt, Databricks, sqlmesh, Datahub, Superset or Snowflake

Expertise in SQL & Python to build data pipelines

Experience building APIs, SDKs, or self-service platforms that other engineers use.

Practical experience using AI development tools to accelerate implementation while maintaining engineering quality.

How you work matters:

You’re a high velocity engineer. You decompose problem spaces into digestible chunks and constantly iterate.

You’re biased toward action. You love to prototype to test ideas and get feedback early, but are okay throwing away bad ideas.

You can quickly build context in unfamiliar areas. You can move between a pipeline, a service, or a developer tool, build enough context to contribute. You also know when to ask for help when it speeds things up.

You balance speed and judgment. You can get a prototype off the ground quickly, but also build a reliable and scalable production system

Technologies We Use:

Data: Trino, Spark, Pinot, Hive, Airflow, Iceberg, Spark, Datahub, Kafka

Storage: S3

Infrastructure: Terraform, AWS

Languages: Python, Go, SQL, Scala, Typescript

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.

Where you’d work

From the office

About the company

Salesforce

  • Industry: SaaS

Offices in San Francisco, United States, New York, United States, Atlanta, United States, Seattle, United States, United States

Also hiring in Austin, United States, Amsterdam, Netherlands, London, United Kingdom and 30 more places

34 of their 332 open roles are remote

Details12 facts · Role, Location, Compensation, Employment, Company
Tech stack
  • Python
  • SQL
  • AWS
  • dbt
  • Kafka
  • Spark
  • Databricks
  • Snowflake
  • Airflow
Seniority
Staff
Type
Full-time
Industry
SaaS
Specialty
Data Engineering
Region
United States
Show 6 more factsShow less

Role

Category
Data & Analytics
Specialty
Data Engineering
Seniority
Staff
Experience
8+ years
Tech stack
  • Python
  • SQL
  • AWS
  • dbt
  • Kafka
  • Spark
  • Databricks
  • Snowflake
  • Airflow

Location

Work model
Office
Region
United States
Offices
  • San Francisco, United States
  • New York, United States
  • Atlanta, United States
  • Seattle, United States
  • United States

Compensation

Salary
Salary by agreement
Pay period
Annual

Employment

Type
Full-time

Company

Industry
SaaS

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