To connect the world, we must reflect the world. At Virgin Hyperloop, we’re bringing together unique perspectives, empowering our community to celebrate all voices, and creating equal opportunities to build, grow, and thrive. 

WHY WE NEED YOU

The Data Engineer will be part of the Machine Intelligence & Analytics Group, within the Software Engineering department. This team works closely with all other teams to develop, deliver and maintain data driven products and backend analytics platforms for the discovery, interpretation, communication, and exploitation of meaningful patterns in data. In addition, this team will develop and maintain an analytics pipeline for acquisition, storage, and processing data types of interest to feed real-time artificial intelligent system behaviors. The Analytics team will architect data systems supporting machine learning applications, develop custom toolchains for analysis and exploration, and work with DevOps and IT to host and scale intelligent applications.

Ultimately, we will design reliable, scalable, real-time (or near-real time) applications that make Virgin Hyperloop One a reality. We are seeking candidates with various levels of experience to join our team of qualified, diverse individuals at our Los Angeles facility.

WHAT YOU'LL DO

• Architect and implement data pipelines (ingestion, batch simulation infrastructure, real-time insights).
• Perform ETL operations on large datasets from many complex, heterogeneous data sources.
• Develop or implement tools to support analyst-driven machine learning analyses.
• Work closely with Algorithms team to prototype AI/ML proof of concepts.
• Participate in design/code reviews to ensure compatibility with architecture.
• Deploy monitoring solutions to detect and resolve problems in real-time.
• Build reporting functionality on results of pipeline analysis and monitoring.
• Maintain quality and accessibility of data products.
• Champion processes and procedures across the organization.
• Develop or modify existing machine learning tools and libraries as needed.
• Develop visualizations of key parameters and relationships to provide insight into data.
• Enhance, scale, and deploy real-time analytics capabilities, models, and visualizations within production environment on production compute architecture.
• Collaborate in a fast-changing environment and communicate clearly and effectively with colleagues who range from data scientists, developers, DevOps, hardware engineers, and product managers.

WHAT YOU'VE DONE

• Bachelor’s degree in Computer Science or a highly quantitative discipline.
• Minimum 1-3 years experience working as a Data Engineer.
• Strong knowledge in software engineering principles.
• Hands on experience and expertise with cloud computing services (AWS, Azure, etc.)
• Working knowledge of distributed computing architectures and databases.
• Working knowledge in manipulating large datasets.
• Strong programming ability with Python, Go and web technologies.
• Agile, fast prototyping skills, including feature integration during all cycles of development.
• Working proficiency and excellent communication skills in verbal and written English.

NICE TO HAVE

• MS Degree in Computer Science or equivalent field.
• Ability with the following programming languages:  Scala, R
• Experience with the following software packages: Tableau, TensorFlow, SQLAlchemy, Flask, PostgreSQL, NoSQL, Apache products (Airflow, Spark, Hadoop, Hive, etc.)
• Familiarity with DevOps and CI pipelines.
• Experience with visualization tools: Seaborn, Bokeh, D3.js
• Experience working with front-end frameworks (Angular, React, etc.).
• Domain expertise and knowledge of transportation, logistics, and autonomous systems.
• Successfully delivered and maintained a major cloud service with a large numbers of end users.

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