Principal Data Engineer, Big Data

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

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.

We are looking for a Principal Data Engineer who is looking for a challenge, 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

• Lead Data Engineer and architect, to design, implement a highly scalable system to ingest and process Petabytes of data per day.
• Design and develop applications for data pipeline and data management.
• Set processes and policies for data governance and data pipeline 
• Architect and implement best practices of big data tools such as Spark, Airflow, Kafka, Presto and Timeseries Databases
• Lead and mentor junior Data and BI engineers. 
• Set and define the standards and best practices in data team
• Be the point of reference for solving a challenging technical problem.
• Architect and implement Machine Learning Pipelines for Data Science team.

Qualifications

• Bachelor or Masters in Software Engineering and Computer Science
• 8+ years of experience in design and development of large-scale data platforms
• 4+ years of software development experience in Scala or Java
• Experience in hands-on implementing new application with production quality
• Expert in containerization, including Docker and Kubernetes
• Expert in tools such as Apache Spark, Apache Airflow, Presto, and Kubeflow
• Proficient in Spark application development
• Expert in design and implementing reliable, scalable, and performant distributed systems and data pipelines
• Extensive programming and software engineering experience, especially with Java, Scala, or Python
• Experience with running large-scale distributed computing infrastructure such as load balancing, Zookeeper, and micro-service architecture
• Experience with security and access management
• Experience with managing distributed databases like Elasticsearch, Cassandra, and timeseries databases
• Experience with a columnar database such as Redshift, Vertica, or Parquet files
• Great verbal and written communication skills