Senior Software Engineer- Data Platform

Requisitos e responsabilidades

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Details

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:

Design, build, and operate high-scale data ingestion and replication systems from Samsara’s primary production data stores, including RDS, DynamoDB, internal APIs, and event-driven systems, into our data lakehouse.
Build and maintain reliable, scalable, and modern data platform infrastructure capable of handling petabytes of data across Samsara’s analytics, AI, product, and operational use cases.
Improve the reliability, observability, scalability, security, and developer experience of Samsara’s Spark and Databricks-based data processing platform.
Develop internal libraries, APIs, frameworks, and tooling in languages such as Go and Python to help teams across Samsara move, process, discover, and access data safely and efficiently.
Work on foundational data lake and lakehouse technologies, including Delta Lake on S3, data catalogs, metadata services, orchestration systems, and platform automation.
Collaborate closely with infrastructure, product engineering, data science, analytics, security, and data engineering teams to understand platform needs and deliver durable, scalable solutions.
Stay connected to modern data platform technologies and help shape Samsara’s long-term data infrastructure roadmap, including support for AI, privacy, security, global scale, and customer-facing data products.
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

In this role, you will:

4+ years of professional software engineering experience in production environments.
4+ years of experience building or maintaining large-scale production data infrastructure, data platforms, distributed systems, or data lake systems.
Strong experience with Apache Spark or similar distributed data processing systems.
Experience operating production infrastructure in AWS, including services such as S3, RDS, DynamoDB, SQS, Kinesis, Lambda, or similar.
Experience designing, building, and operating reliable systems with strong ownership of scalability, observability, security, and operational excellence.
Proficiency in at least one production programming language such as Go, Python, Scala, or Java.
Ability to collaborate effectively with cross-functional partners, including software engineers, data scientists, analysts, security teams, and product stakeholders.

In this role, you will:

Experience with Databricks, Delta Lake, or similar lakehouse technologies such as Iceberg or Hudi.
Experience building data replication or ingestion systems from OLTP data stores into a data lake or lakehouse.
Experience with Infrastructure-as-Code tools such as Terraform or CloudFormation.
Familiarity with data catalogs, metadata systems, and data discovery tools such as Unity Catalog, Hive Metastore, DataHub, or Amundsen.
Experience with orchestration systems such as Airflow, Dagster, or Prefect.
Experience with streaming data, event-driven architectures, or systems that handle late-arriving or mutable data.
Familiarity with containerization or orchestration technologies such as Docker, Kubernetes, ECS, or Fargate.
Experience building internal platforms, libraries, or developer tooling used by other engineering teams.
Experience contributing to data infrastructure roadmaps, evaluating new technologies, and driving improvements that create leverage for internal and external customers.

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