Senior Data Engineer

Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.

Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.

About the role:

Data and Analytics is a critical team within Business Technology. Our mission is to enable integrated data layers for all of Samsara with the insights, tools, infrastructure to make data-driven decisions. We are a growing team that loves all things data — composed of data engineers, architects, analysts, and data scientists.

We are looking for a Senior Data Engineer who brings a software engineers mindset to data infrastructure. This isnt just a pipeline-builder role — were looking for someone who thinks in systems, builds platforms others can extend, and is excited about pushing the boundaries of what data engineering looks like in an AI-first world. Youll architect Spark-driven workflows at scale, design data platforms as products, and build the next generation of intelligent tooling including MCP servers and AI agents that automate and accelerate data engineering workflows.

Our team promotes an agile, collaborative, and supportive environment where diverse thinking, innovative design, and experimentation are welcomed and encouraged.

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 keep the lights on, get food into grocery stores, reduce emissions, and ensure workers return home safely.

• You are the architect of your own career: If you put in the work, this role wont be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development and mastery in a hyper-growth environment.

• Youre energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas.

• You want to build platforms, not just pipelines: You think about data infrastructure as a product, care deeply about developer experience, and want to shape how an engineering team works with data at scale.

• Youre excited about AI-augmented engineering: You want to be at the frontier of how AI agents and intelligent tooling change the way data engineers work.

In this role, you will: 

Data Platform Engineering

• Develop and maintain end-to-end data pipelines and backend ingestion workflows, and participate in the build of Samsaras Data Platform to enable advanced automation and analytics.

• Work with data from a variety of sources including ERP(Netsuite), CRM(Salesforce), Product, Order Flow, and Support ticket data.

• Manage critical data pipelines to enable growth initiatives and advanced analytics.

• Facilitate data integration and transformation for moving data between applications, ensuring interoperability with data layers and the data lake.

• Develop and improve data architecture, data quality, monitoring, observability, and data availability.

• Write data transformations in SQL/Python to generate data products consumed by Analytics, Marketing Operations, and Sales Operations teams.

Spark & Distributed Systems

• Design, build, and operate large-scale Spark and PySpark workflows for batch and streaming data processing across Databricks and cloud environments.

• Optimize Spark job performance — tuning partitioning, shuffle, caching, and resource allocation for production-grade reliability and efficiency.

Platform & Systems Thinking

• Define and enforce data engineering standards, patterns, and best practices across the team.

• Design systems with long-term maintainability in mind: clear contracts, testable components, and thoughtful failure modes.

• Collaborate with platform and infrastructure teams to evolve the underlying architecture of Samsaras enterprise data ecosystem.

MCP Servers & AI Agents

• Build and maintain MCP (Model Context Protocol) servers that expose Samsaras data assets and engineering workflows to AI models and internal tooling.

• Collaborate with platform teams to integrate agentic workflows into the data engineering lifecycle.

• Evaluate and adopt emerging AI-native tooling for data engineering, staying ahead of the curve on how LLMs and agents can accelerate data work.

Leadership & Collaboration

• Champion, role model, and embed Samsaras cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally.

• Provide mentorship to junior team members and deliver technical guidance, training, and knowledge-sharing across teams.

• Engage directly with internal cross-functional stakeholders to understand their data needs and design scalable solutions.

• Lead end-to-end projects as the central point of contact for stakeholders.

Minimum requirements for the role:

• Bachelors degree in computer science, data engineering, data science, information technology, or an equivalent engineering program.

• 8+ years of work experience as a Software Engineer with data focus or as Data Engineer.

• 5+ years of experience building and maintaining large-scale, production-grade end-to-end data pipelines, including Data Modeling.

• 5+ years of hands-on Spark / PySpark in a production environment, including job optimization and performance tuning.

• Core Engineering Fundamentals: Strong programming capabilities in Python and SQL, combined with cloud data warehouse/lakehouse experience (e.g., Snowflake, Google BigQuery, Databricks, or Apache Iceberg).

• Exposure to ETL tools such as Fivetran, DBT, or equivalent.

• API experience: Python-based API frameworks for data pipeline ingestion.

• RDBMS experience: MySQL, AWS RDS/Aurora, PostgreSQL, Oracle, MS SQL Server, or equivalent.

• Cloud: AWS, Azure, and/or GCP.

An ideal candidate also has experience in:

• Designing and governing a centralized semantic layer for reliable AI and analytics

• Logging and monitoring experience: Splunk, DataDog, AWS CloudWatch, or equivalent.

• AWS Serverless: API Gateway, Lambda, S3, SNS, SQS, SecretsManager.