About the role:

Samsara is seeking a Senior Software Engineer to join our Data Platform team. This team is pivotal in building and maintaining the infrastructure that underpins the diverse data requirements of Samsara's entire analytics ecosystem, coming from engineers, data scientists, product managers, and others. We are looking for a Senior Engineer with proven expertise in near real-time data streaming and analytical infrastructure to support queries from reporting features in customer-facing web applications.

Some of the team responsibilities include:

• Managing Samsara’s Databricks & associated AWS environment
• Replicating data sources (e.g MySQL, Dynamo) to our data lake
• Developing and maintaining infrastructure that supports complex data analyses and insights within Samsara's product offerings
• Implementing robust data governance and security measures to ensure data integrity and compliance

This role can be fully remote in Canada.

You should apply if:

• You want to impact the industries that run our world: The software, firmware, and hardware you build 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 want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world's physical operations.
• You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
• You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
• You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win together.

In this role, you will:

• Develop software to reliably ingest vast amounts of data into our data lake.
• Explore new infrastructure needed to support the growing needs of our data platform.
• Expand our ability to stream data into the data lake to support near real-time access and stand up a streaming ecosystem from scratch.
• Be responsible for the uptime, reliability, and monitoring of our data platform.
• Uplevel team members and cross-functional colleagues on topics like data best practices, AWS, Spark, etc.
• Collaborate with cross-functional engineering partners to accurately determine data requirements and ensure the delivery of fresh, and low-latency streaming data for our customer-facing reports system.
• 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 and across new offices.

Minimum requirements for the role:

• BA/MS degree in Computer Science, Statistics, or a related discipline.
• 5+ years experience in a data infrastructure of platform-focused role.
• Experience building a large-scale production-grade data platform (including a Data Lake) for data scientists, analysts, and engineers.
• Demonstrated experience with Terraform or similar infrastructure as code.
• Demonstrated experience in real-time streaming.
• Experience with Spark-based data platforms.
• Previous experience working in a public cloud (e.g AWS, GCP, Azure).
• Experience with version control systems such as Git/GitHub.

An ideal candidate also has:

• Familiarity with time series data and late-arriving data.
• Experience standing up and operating large streaming application pipelines (Spark streaming or Flink).
• Knowledge of Databricks & Delta Lakes.
• Experience working on real-time aggregate reporting in production environments.
• Exposure to complex data, including ML outputs and/or client-side signals.