Engineering Manager, Data Engineering & Infrastructure

Lucid Motors•Newark, NJ

About The Position

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 Engineering Manager, Data Engineering & Infrastructure leads a team of data engineers, and infrastructure engineers supporting Powertrain, Battery, and Manufacturing Engineering. This role combines people leadership, technical direction, and architectural ownership of data platforms and cloud/on-prem infrastructure. The Engineering Manager is accountable not only for defining and guiding the technical direction of data architecture and infrastructure, but also for the day-to-day effectiveness, growth, and delivery of the engineering team. This includes mentoring engineers, providing ongoing technical guidance, supporting daily execution, and establishing clear technical standards and priorities. Success in this role requires being close enough to the work to coach engineers and guide technical decisions, while operating at the appropriate level to align roadmaps, stakeholders, and long-term platform strategy.

Requirements

10+ years of professional experience in data engineering, infrastructure engineering, or closely related technical fields.
Demonstrated experience managing and mentoring data engineering and/or infrastructure engineering teams.
Strong technical background in data platforms, data pipelines, and analytics infrastructure.
Experience providing hands-on technical guidance, including architecture and design reviews.
Familiarity with cloud infrastructure (e.g., AWS) and hybrid on-prem/cloud environments.
Ability to work effectively across engineering, IT, security, and operations organizations.

Nice To Haves

Experience supporting manufacturing, industrial, or test-heavy engineering environments.
Familiarity with analytics and data platforms such as Dremio, Iceberg, InfluxDB, or equivalent technologies.
Experience with factory systems (e.g., Ignition, MES) and manufacturing data pipelines.
Background in automotive, EV, or industrial engineering environments.

Responsibilities

Directly manage, mentor, and develop data engineering and infrastructure engineers, supporting both technical growth and career progression.
Provide consistent technical mentorship, including architecture discussions, design reviews, and guidance on implementation trade-offs.
Set clear expectations for engineering quality, operational ownership, documentation, and reliability.
Establish and maintain effective team operating rhythms (standups, planning, retrospectives) that balance execution with sustainable delivery.
Foster a collaborative, inclusive engineering culture that emphasizes learning, accountability, and continuous improvement.
Own and guide the technical direction of data platforms and infrastructure supporting Powertrain, Battery, and Manufacturing Engineering.
Serve as a technical leader and sounding board for engineers, helping shape scalable, reliable, and maintainable system designs.
Ensure architectural decisions are well-documented, communicated, and consistently applied across the team.
Balance near-term delivery needs with long-term platform health, scalability, and maintainability.
Own prioritization, planning, and delivery across data engineering and infrastructure workstreams.
Actively unblock engineers by resolving cross-team dependencies with IT, Cloud, Security, Manufacturing, and Test organizations.
Translate engineering and business needs into clear technical roadmaps and executable plans.
Maintain appropriate visibility into execution details, stepping in when technical risk, ambiguity, or complexity is high.
Ensure reliable operation of data pipelines, analytics platforms, and infrastructure supporting manufacturing and test environments.
Lead incident response for data or infrastructure issues, including post-incident reviews and follow-up actions.
Champion best practices for security, access management, observability, documentation, and operational readiness.