Data & Analytics Engineer building scalable data platforms for Ledgebrook, an insurance company. Designing pipelines, governance, and cloud data systems while partnering with technical and insurance teams.
About the role
- Senior Software Engineer on Data Platform developing and maintaining infrastructure for data ingestion and processing. Collaborating on projects that drive AI and analytics initiatives at Samsara.
Responsibilities
- 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.
Requirements
- 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.
Benefits
- A flexible, employee-led remote model
- Professional development stipend
- Comprehensive health and parental leave plans
- Initial RSU grant with no vesting cliff
- Ongoing refresh opportunities tied to performance
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