Principal Software Engineer, Data Platform

Salesforce

Remote

Quick summary

Work type
Remote
Location
San Francisco, CA
Salary
$197,300–$313,700 / yr
Posted
40 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $191k
This role $256k
$139k most similar roles pay here $332k

This role pays more than 90% of similar roles. Most pay $161,500–$220,094 — the shaded band above. At the midpoint, this role pays about $256k versus about $191k for comparable roles.

Based on 240 similar postings.

Employer

About Salesforce

Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing

Salesforce currently has 86 open roles on FindRole.

Listed pay typically runs $148,500–$260,100 across 77 roles with salary data.

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At a glance

TL;DR · Principal Software Engineer, Data Platform

The Principal Member of Technical Staff for Salesforce's Enterprise Data Platform is a high-impact individual contributor role responsible for modernizing and optimizing the company’s foundational data ecosystem. This technical architect will lead engineering teams by bridging modern distributed analytics with Semantic AI, using technologies like Snowflake, dbt, Informatica, Airflow, Neo4j, and TopQuadrant to design scalable knowledge graphs and seamless data flows into BI and advanced analytics platforms. Key responsibilities include defining long-term architecture, ensuring infrastructure as code practices, optimizing performance, enabling AI integration, and setting engineering standards through mentorship and technical influence. Ideal candidates have over 10 years of software engineering experience with a focus on backend distributed systems or large-scale data infrastructures, expertise in Python, Java, Go, Snowflake internals, dbt macros, Airflow scheduler, Neo4j Cypher, and cloud-native services like AWS/GCP and Kubernetes.

What you'll do

  • Define long-term technical architecture for the Enterprise Data Platform.
  • Architect and review Terraform/Helm configurations to ensure infrastructure immutability.
  • Optimize query planners and data serialization formats across Snowflake and Spark.
  • Design integration patterns for AI-assisted tooling within developer workflows.
  • Lead technical design of Graph RAG, enabling LLM agents to query structured data.
  • Set standards for code quality and enforce strict CI/CD pipelines with unit testing.
  • Mentor senior engineers through design reviews and pair programming sessions.

What we're looking for

  • 10+ years of software engineering experience, with expertise in backend distributed systems and data infrastructure.
  • Deep knowledge of Snowflake, dbt, Airflow, Tableau, Neo4j, and related technologies for large-scale data platforms.
  • Proven ability to design and optimize complex data architectures, including performance tuning and scalability solutions.
  • Expertise in cloud-native services (AWS/GCP) and container orchestration (Kubernetes/EKS).
  • Experience with AI/LLM integration, including RAG architecture and vector databases.
  • Strong coding skills in Python, Java, or Go, along with the ability to mentor senior engineers.

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