WHO WE ARE:

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. For the first time ever, safety, operations and finance teams can manage their drivers, vehicles, equipment, and fleet related spend in a single system. Combined with industry leading AI, the Motive platform gives you complete visibility and control, and significantly reduces manual workloads by automating and simplifying tasks.
Motive serves more than 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries, including transportation and logistics, construction, energy, field service, manufacturing, agriculture, food and beverage, retail, and the public sector.
Visit gomotive.com to learn more.

ABOUT THE JOB:

As a Principal Data Platform Engineer, you will be involved and responsible for full ownership and driving key data platform initiatives and life cycle of the data management including data ingestion, data processing, data storage, querying system, cost reduction efforts towards delivering product features to internal and external Motive customers.
We are looking for a technical leader in the Data Platform area who has built the full data ingestion, transformation and analytics systems over AWS and Kubernetes in multiple companies. This individual would have faced and solved multiple challenges affecting many feature areas during this process using the best practices. This individual will be responsible for contributing significantly to drive the Motive’s Data Platform vision.
The Data Platform team works in three areas: 1. Build scalable systems and services for data ingestion, access, processing and query to enable data driven product features. 2. Collaborate and work closely with the various stakeholders and our backend product teams to improve and add features to the platform.

• Work with other leaders in the Platform area to define and plan out the long term strategy for Data Platform.
• Design and develop scalable distributed systems and frameworks for data management
• Focus on addressing fault-tolerance and high availability issues, and work on scaling ingestion pipelines, improving and adding features to ETL framework while maintaining SLAs on performance, reliability, and system availability.
• Collaborate with engineers across teams to identify and deliver cross-functional features
• Participate in all aspects of the software development life cycle, from design to implementation and delivery.