Staff Data Engineer — Metrics Platform & AI Foundations

Slack; New York (NY); On-site; USD 197,000 - 314,000; Full time

Job summary

Salesforce is seeking a Staff Data Engineer to shape the metrics foundation across Product, Analytics, Marketing, Sales, and Operations. You’ll set direction for ingestion, semantics, and serving, partnering with product, data science, and engineering to define and govern metrics with clear SLAs and quality metrics.

You will lead architecture for scalable data models, mentor senior engineers, and drive cross‑functional initiatives that impact multiple teams and quarters.

Qualifications

• 10+ years of software or data engineering experience, including 6+ years in data architecture and modeling.
• Led multi‑team initiatives as an IC and aligned engineering, product, data science, and analytics.
• Deep SQL expertise, Python, and working knowledge of Go/Java/Scala.
• Hands‑on with Spark, Trino, Airflow, Iceberg, and Snowflake; dimensional and star/snowflake modeling.

Responsibilities

• Set architecture and roadmap for metrics platform including ingestion, semantic layer, and serving.
• Design and scale data models and pipelines with billions of records; ensure quality and SLAs.
• Evolve semantic layer; build APIs/tools for metric definitions, lineage, and queries.
• Lead metric certification and governance; mentor senior engineers; leverage AI in development.

Skills

SQL

Python

Go/Java/Scala

Data modeling

Education

Technical degree

Tools

Spark

Trino

Airflow

Iceberg

Snowflake

dbt

Datahub

Cube

LookML

Job description

Salesforce is seeking a Staff Data Engineer to shape the metrics foundation across Product, Analytics, Marketing, Sales, and Operations. You’ll set direction for ingestion, semantics, and serving, partnering with product, data science, and engineering to define and govern metrics with clear SLAs and quality metrics.

You will lead architecture for scalable data models, mentor senior engineers, and drive cross‑functional initiatives that impact multiple teams and quarters.