
Senior AI Data & Analytics Engineer II
About this role
This remote position is based in New York City and requires residency in the United States. It suits an experienced data professional looking to build the underlying data foundation for AI and analytics at Samsara.
Role Overview
Samsara seeks a Senior AI Data & Analytics Engineer II to join the Marketing Data and Analytics Engineering team. The professional in this role will shape the technical roadmap, architect core data infrastructure, and develop autonomous agents and data products that support marketing, sales, and research and development operations.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
About the Company
Samsara operates the Connected Operations Cloud, which is a platform enabling organizations that rely on physical operations to utilize Internet of Things data for actionable insights. The company focuses on improving the safety, efficiency, and sustainability of physical operations across sectors such as agriculture, construction, field services, manufacturing, and transportation.
How to Apply
Candidates should apply on the official company careers page.
Skills and tech stack
Questions candidates ask
Where is this job located?
This position is remote with a location designation of Remote - NYC and is open to candidates residing in the United States.
What is the salary range for this position?
The annual base salary range is $137,445 to $231,000 USD, with exact pay varying based on factors such as city of residence, knowledge, skills, and experience.
How many years of experience are required?
Candidates must have 8 or more years of experience in data engineering, analytics engineering, or AI engineering.
What benefits and equity options are available?
Employees are eligible for an initial RSU grant with no vesting cliff, performance-based equity refresh opportunities, a professional development stipend, comprehensive health plans, and parental leave.
What specific technical proficiencies are expected?
The role requires expert-level Python and SQL, hands-on DBT and data modeling experience, familiarity with modern lakehouse architectures like Databricks, and experience with production LLM or agent systems.