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Job Description
The role involves leading the design and development of Samsara's developer ecosystem, focusing on data integration, API frameworks, and scalable data streaming systems to support the company's AI and data strategies, ultimately enabling scalable, intelligent solutions for global physical operations.
Key Responsibilities
- Architect and guide high-impact, cross-functional initiatives for external integrations, including core developer APIs, Eventing, Lambdas, and Marketplace.
- Develop and evolve the data integration strategy, including the design of data pipelines using Kafka and related technologies.
- Design and implement serverless compute architectures using AWS Lambda to enable complex logic execution.
- Establish and oversee the technical vision and architectural governance for external API frameworks to ensure scalability and developer experience.
- Mentor senior engineers, lead design reviews, and align stakeholders on technical direction.
- Partner with leadership and enterprise customers to define and execute multi-year technical strategies for the developer and data platforms.
Requirements
- Deep, systems-level expertise in designing, building, and operating high-throughput, large-scale data streaming systems e.g., Kafka.
- Proven experience in architecting and implementing AI-first data strategies, with a strong understanding of how event streams Kafka integrate with data lakes and data warehouses in a modern LakeHouse architecture.
- Demonstrable experience with serverless compute architectures e.g., AWS Lambda and their associated design patterns and trade-offs.
- Extensive experience in designing, building, and providing governance for large-scale, public-facing APIs, with a preference for GraphQL.
- A track record of leading complex, multi-team, and multi-quarter technical initiatives from inception to delivery.
- Experience with managed event streaming platforms e.g., Amazon MSK, Azure Event Hubs, Google Cloud Pub Sub.
- Deep familiarity with cloud data warehousing and data lake solutions e.g., Snowflake, Databricks.
- Experience with ML AI model deployment and MLOps infrastructure.
- Minimum of 3 years of experience in designing, building, and operating high-throughput, large-scale data streaming systems.
- Minimum of 2 years of experience in architecting and implementing AI-first data strategies.
- Minimum of 2 years of experience with serverless compute architectures such as AWS Lambda.
- Minimum of 2 years of experience in designing, building, and providing governance for large-scale, public-facing APIs.
- Experience leading technical initiatives across multiple teams and quarters from inception to delivery.
Benefits & Perks
Full time employees receive a competitive total compensation package
Employee-led remote and flexible working
Health benefits
Flexible working model that supports remote work, in-person, or hybrid arrangements
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