About the role:
Samsara’s Revenue Operations AI & Data Team is building the future of how we go to market — with intelligence, personalization, and speed. We’re a high-impact team of builders, scientists, and strategists focused on transforming sales operations through AI. Our mission is to help sellers reach the right customer at the right time with the right message — and to put everything they need at their fingertips, whether that’s data from Salesforce, context from a past call, or content that wins deals.

As a Sr. Data Engineer, you’ll own the data platforms that power Samsara’s GTM AI engine. You’ll be responsible for building, scaling, and optimizing our Databricks data store, visualization store, and AI store, while also enabling large-scale generative AI jobs in Databricks. Your work will ensure that our AI applications are grounded in clean, reliable, and well-structured data — from CRM pipelines to GenAI-powered copilots. You’ll partner closely with data scientists, AI engineers, and business stakeholders to deliver the infrastructure that fuels innovation at scale.

This is a remote position open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area.    

You should apply if: 

• You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
• You have an innate curiosity about how businesses work: One day you’ll meet with someone in waste management and the next you may be learning about the inner workings of a food distribution center. Our top sales team members seek to learn the ins and outs of the businesses they support in order to make a larger impact. 
• You build genuine relationships with your customers: The industries we serve have relied on pen-and-paper solutions for years and haven’t been met with the type of technology we offer. Our customers value earned trust and human relationships built over time.
• You want to be with the best: Samsara’s high-performance culture means you’ll be surrounded by the best and challenged to go farther than you have before.

In this role, you will: 

• Own and operate our Databricks data store, ensuring performance, scalability, and reliability.
• Build and manage a visualization store and AI store that empower downstream analytics, machine learning, and AI applications.
• Design and optimize bulk GenAI data pipelines in Databricks to support generative AI applications at scale.
• Partner with AI engineers and data scientists to enable experimentation, model training, and production-grade deployments.
• Develop frameworks for data ingestion, transformation, governance, and monitoring across CRM, sales, and revenue systems.
• Collaborate with cross-functional teams to ensure data infrastructure meets both technical and business needs.

Minimum requirements for the role:

• 5+ years of industry experience in data engineering, with significant experience building large-scale data platforms.
• Deep expertise in Databricks, Spark, and modern data lakehouse architectures.
• Proficiency in Python and SQL, with experience in designing robust ETL/ELT pipelines.
• Experience orchestrating data workflows at scale and enabling machine learning or AI use cases.
• Strong understanding of data modeling, performance optimization, and cost-efficient infrastructure design.
• Located in and authorized to work in the United States (this is a fully remote role).

An ideal candidate also has:

• Experience enabling generative AI workflows in Databricks or similar platforms.
• Familiarity with vector databases, embeddings, and retrieval systems.
• Experience with Salesforce, Gong, Outreach, or other CRM/enablement tools as data sources.
• Track record of owning and scaling mission-critical data infrastructure in a high-growth environment.
• Exposure to observability, monitoring, and governance best practices for data and AI systems.
• Ability to collaborate closely with AI/ML teams while driving technical excellence in data engineering.