Lucid Careers

Senior Infrastructure Engineer, Data Platform

Data Engineering

Newark, CA      Full-Time

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Leading the future of luxury mobility

Lucid’s mission is to inspire the adoption of sustainable energy by creating the most captivating luxury electric vehicles, centered around the human experience. Working at Lucid Motors means having a shared vision to power the future in revolutionary ways. Be part of a once-in-a-lifetime opportunity to transform the automotive industry.

We are looking for a Senior Infrastructure Engineer who enjoys thinking big and looking to make their mark on an extremely fast growing company. If building large and building fast, working with a young and very talented team of engineers and collaborating with the brightest mind in the Automotive industry is what you like, Lucid is the best to experience it.

The Role

  • Design and implement highly scalable infrastructure for data processing platform using Kubernetes
  • Implementing security, permissions, authentication and relevant InfoSec activities
  • Setting up Gateways, load balancers, TCP and UDP sockets
  • Containerization and deployment of microservices on Kubernetes
  • Setup and monitor application access and connectivity.
  • Auto scale and monitoring performance for Kubernetes and running applications using Prometheus and Grafana or similar tools.
  • Performing SRE activities such as availability and reliability monitoring and reports.
  • Deploy and configure tools such as Kafka, Spark, Presto, Airflow, MQTT and Microservices.
  • Setting up infrastructure as a service using Terraform
  • Contribute and setup CI/CD process
  • Setting up and operate Artifact repository such as Artifactory and JFrog
  • Operate and Setup code repository with GitLab or Bitbucket


  • Bachelor or Masters in Computer Science or relevant experience
  • Proven experience working with large scale data platforms
  • Experienced with security and access management
  • Experienced in design and implement reliable, scalable, and performant distributed systems and data pipelines
  • DevOps experience implementing large scale data stacks using Git, Jenkins, Docker
  • Extensive programming experience, especially in Bash, Java, Python, and/or C++
  • Experience with containerization, including Docker and Kubernetes
  • Experience with running large-scale distributed computing infrastructure such as Spark, Hive, Presto, Zookeeper and Kafka
  • Experience with managing distributed systems like Elasticsearch, Logstash, Kibana (ELK)
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