AI Engineer, Finance & Strategy — Data Foundations

Samsara; San Francisco, Northern (CA, KY); Hybrid; USD 146,000 - 246,000; Full time

Job summary

Samsara seeks a senior data & AI leader for Finance & Strategy to own the data foundation and drive scalable, secure AI-enabled processes. You will coordinate with Finance, BizTech, PeopleOps and Accounting to transform data from NetSuite, Workday, Adaptive and Salesforce into production-grade decision systems.

You'll design end-to-end data pipelines, implement governance, and empower stakeholders with reliable analytics while advancing the enterprise analytics agenda in a fast-growing public

Qualifications

• Bachelor's degree in CS/Engineering/Info Systems or equivalent experience.
• 8+ years building and scaling production-grade data pipelines and enterprise apps.
• Hands-on experience with large language model (LLM) apps and prompt engineering.
• Proficiency in Python and SQL; experience with Databricks and major financial systems.

Responsibilities

• Own the data foundation and AI roadmap for Finance & Strategy.
• Design, build, and maintain pipelines and integrations across financial systems.
• Extend AI-powered tools across core finance processes — forecasting and planning.
• Lead cross-functional alignment on system workstreams across Finance, BizTech, PeopleOps, Accounting.
• Establish data governance and quality standards to drive close-cycle improvements.

Skills

Python

LLM apps

SQL

Databricks

Workday

NetSuite

Adaptive

Salesforce

Data pipelines

APIs

Education

Bachelor's degree in CS/Engineering/Info Systems/Finance

Tools

Databricks

NetSuite

Workday

Adaptive

Salesforce

Google Suite

Slack

Job description

Samsara seeks a senior data & AI leader for Finance & Strategy to own the data foundation and drive scalable, secure AI-enabled processes. You will coordinate with Finance, BizTech, PeopleOps and Accounting to transform data from NetSuite, Workday, Adaptive and Salesforce into production-grade decision systems.

You'll design end-to-end data pipelines, implement governance, and empower stakeholders with reliable analytics while advancing the enterprise analytics agenda in a fast-growing public