Senior Software Engineer - Data Platform

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
Minimum requirements for the role:

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.
An ideal candidate also has:

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.

Skills Required
4+ years professional software engineering experience in production environments.
4+ years 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 (S3, RDS, DynamoDB, SQS, Kinesis, Lambda, or similar).
Experience designing, building, and operating reliable systems with 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 (engineers, data scientists, product, security).
Reside in the United States (remote, US candidates only).
Experience with Databricks, Delta Lake, or similar lakehouse technologies (Iceberg, Hudi).
Experience building data replication/ingestion systems from OLTP stores into a data lake or lakehouse.
Experience with Infrastructure-as-Code (Terraform or CloudFormation).
Familiarity with data catalogs/metadata systems (Unity Catalog, Hive Metastore, DataHub, Amundsen).
Experience with orchestration systems (Airflow, Dagster, Prefect).
Experience with streaming/event-driven architectures and late-arriving or mutable data.
Familiarity with containerization and orchestration (Docker, Kubernetes, ECS, Fargate).
Experience building internal platforms, libraries, or developer tooling used by other engineering teams.