Senior Data Engineer II

About the Role

The data and AI team is a critical function 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, AI engineers, architects, analysts, and data scientists.

We are looking for a Senior Data Engineer II who brings a software engineer's mindset to data infrastructure. This isn't just a pipeline-builder role — we're 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. You'll manage data APIs, 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 role is open to candidates residing in the US and Canada except the San Francisco Bay Area and New York Metro City.

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 won't 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.
• You're 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.
• You're 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 Engineering

• Develop and maintain end-to-end data pipelines and backend ingestion workflows, and participate in the build of Samsara's 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.
• 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.

Data APIs

• Design, build, and manage data APIs in python using frameworks such as FastAPI.
• Manage API runtime in AWS ecosystems- Lambda and RDS.
• Monitor and optimize API , track observability via tools such as Data Dog or Splunk.
• Production Support - participate in on-call rotations and act as technical escalation point of contact for data quality issues , API uptimes etc.

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 Samsara's enterprise data ecosystem.

MCP Servers & AI Agents

• Build and maintain MCP (Model Context Protocol) servers that expose Samsara's 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 Samsara's 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

• Bachelor's degree in computer science, data engineering, data science, information technology, or an equivalent engineering program.
• 10+ years of work experience as a Software Engineer with data focus or as Data Engineer.
• 8+ 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.
• 3+ years of hands-on experience developing and managing APIs, preferably in python.
• 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 , API management tools.
• RDBMS experience: MySQL, AWS RDS/Aurora, PostgreSQL, Oracle, MS SQL Server, or equivalent.
• Cloud: AWS, Azure, and/or GCP.

Additional Strengths

• 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.