Software Engineer - Data Platform

samsara; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Samsara is seeking a remote, US-based Software Engineer for a data platform team that builds and operates the core infrastructure for ingesting, processing, and serving petabyte-scale data. This role focuses on distributed systems, lakehouse technologies, and developer-facing platform tooling, not BI.

You will design pipelines, work with Spark/Databricks, Delta Lake on S3, and internal libraries in Go and Python to enable data access across analytics, AI, and product engineering use cases.

Qualifications

• Background as a software engineer with experience building and operating production data platforms, distributed systems, or large-scale ingestion infrastructure.
• Hands-on experience with Spark, Databricks, and Delta Lake on S3, plus replication from sources such as RDS and DynamoDB.
• Proficiency in Go and Python for building internal platform tooling, libraries, and APIs.

Responsibilities

• Design, build, and operate high-scale ingestion and replication pipelines that move data from primary production stores into a data lakehouse.
• Build and maintain reliable, scalable infrastructure across Spark and Databricks that handles petabytes of data for analytics, AI and operational workloads.
• Improve the reliability, observability, scalability, security, and developer experience of the data processing platform.
• Develop internal libraries, APIs, frameworks, and tooling in Go and Python to help other teams move, process, discover, and access data safely.
• Work on foundational lakehouse technologies including Delta Lake on S3, data catalogs, metadata services, orchestration systems, and platform automation.
• Partner closely with infrastructure, product engineering, data science, analytics, security, and data engineering teams to understand platform needs and deliver durable solutions.

Skills

Go

Python

Spark

Databricks

Delta Lake

RDS

DynamoDB

Distributed systems

Tools

Delta Lake on S3

RDS

DynamoDB

APIs

Job description

Role overview

A remote, US-based software engineering role on a data platform team that builds and operates the foundational infrastructure for ingesting, processing, and serving petabyte-scale data. The work supports analytics, AI, and product engineering use cases across the business and is not a BI or analytics engineering position. It centers on distributed systems, lakehouse technologies, and developer-facing platform tooling.

Responsibilities

• Design, build, and operate high-scale ingestion and replication pipelines that move data from primary production stores (RDS, DynamoDB, internal APIs, and event-driven systems) into a data lakehouse.
• Build and maintain reliable, scalable infrastructure across Spark and Databricks that handles petabytes of data for analytics, AI and operational workloads.
• Improve the reliability, observability, scalability, security, and developer experience of the data processing platform.
• Develop internal libraries, APIs, frameworks, and tooling in languages such as Go and Python to help other teams move, process, discover, and access data safely.
• Work on foundational lakehouse technologies including Delta Lake on S3, data catalogs, metadata services, orchestration systems, and platform automation.
• Partner closely with infrastructure, product engineering, data science, analytics, security, and data engineering teams to understand platform needs and deliver durable solutions.

Requirements

• Background as a software engineer with experience building and operating production data platforms, distributed systems, or large-scale ingestion infrastructure.
• Hands-on experience with Spark, Databricks, and Delta Lake on S3, plus replication from sources such as RDS and DynamoDB.
• Proficiency in Go and Python for building internal platform tooling, libraries, and APIs.
• Familiarity with data catalogs, metadata services, and orchestration systems within the big data ecosystem.
• Ability to collaborate across infrastructure, product, security, analytics, and data science teams.
• Awareness of modern data platform trends relevant to AI, privacy, security, and global scale.

Nice to have

• Experience designing for AI and analytics roadmaps and supporting model training and operational insights workloads.

Benefits and work setup

Fully remote role open to candidates residing in the US. Relocation assistance is not offered. The team operates with a flexible working model that supports in-person, hybrid, or fully remote work depending on role needs.