Lead Technical Expert, Vehicle Data Strategy

Leading the future in luxury electric and mobility At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.   We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.   Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.

The Lead Technical Expert, Vehicle Data Strategy will drive the strategy and technical roadmap for managing vehicle-generated data, ensuring it is collected, transferred, processed, stored, and utilized efficiently. This role focuses on building a data ecosystem that maximizes the impact of vehicle data on diagnostics, customer support, cloud services, and analytics while balancing performance and cost optimization. The ideal candidate will work closely with product, engineering, and support teams to shape a scalable approach to data management that supports cost objectives, product quality, operational insights, and business scale.

*** This role can be based out of any of the following offices: Newark, CA, Seattle, WA, and Southfield, MI. ***

Responsibilities:

1. Vehicle Data Strategy and Cost-Optimized Roadmap

o Define and lead a strategic roadmap for end-to-end vehicle data management, focusing on efficient data collection, transfer, processing, storage, and analysis.

o Lead a cross functional team of data scientist, engineers, and analysts to plan and execute against a roadmap

o Develop data governance frameworks that ensure data quality, compliance, and security while controlling costs across the data lifecycle.

o Collaborate with product, engineering, and cloud teams to align the vehicle data strategy with business objectives, regularly assessing cost and performance impact.

2. Targeted Data Collection and Requirements

o Partner with cross-functional teams to identify high-value vehicle data necessary for diagnostics, predictive maintenance, remote support, and cloud services, balancing data quality with collection efficiency.

o Establish guidelines to prioritize critical data for collection, reducing unnecessary volume and ensuring data aligns with product and customer support needs.

3. Efficient Data Transfer, Processing, and Storage

o Lead initiatives to streamline data transfer from vehicles to the cloud, minimizing latency, improving reliability, and managing bandwidth costs.

o Identify scalable and cost-effective storage solutions, utilizing strategies like tiered storage, compression, and archiving to balance cost and accessibility.

o Oversee data pipelines for real-time and batch processing, ensuring they are optimized for both performance and cost-effectiveness.

4. Enabling Valuable, Cost-Effective Data Insights

o Collaborate with data scientists, engineers, and business intelligence teams to make vehicle data accessible and actionable, enabling advanced analytics, predictive insights, and operational intelligence.

o Develop data models and schemas that support high-value analytics while optimizing resources and minimizing processing costs.

5. Stakeholder Collaboration and Strategic Cost Management

o Serve as the central point of contact for vehicle data initiatives, ensuring alignment and clear communication with product, engineering, cloud, and support teams around cost-effective data usage.

o Guide decisions on data architecture, tools, and systems that support both efficient data management and long-term cost savings.

6. Data Security, Compliance, and Cost-Conscious Governance

o Implement data governance policies to uphold data quality, privacy, and regulatory compliance while focusing on efficient, cost-conscious practices.

o Proactively address data privacy, security, and compliance in ways that protect customer data and minimize risks without driving up costs.

 

Requirements:

· Bachelor’s or Master’s degree in Data Science, Computer Science, Automotive Engineering, or related field.

· 10+ years of experience in data management, data engineering