Data Engineer

Veeva Systems Logo

Veeva Systems

πŸ“Remote - South Korea

Summary

Join Veeva Systems, a leading life sciences industry cloud company, as a Data Engineer. You will design and build reusable data pipelines using cloud-based and proprietary platforms, collaborating with data scientists on AI/ML implementations. Responsibilities include creating documentation, training data analysts, working with other engineering teams, guiding junior engineers, and ensuring data security. The ideal candidate possesses a BS degree in a related field, 4+ years of data engineering experience, and expertise in cloud-based data pipelines and data modeling. Veeva offers a flexible "work from anywhere" policy and a global presence.

Requirements

  • BS degree in Computer Science, Engineering, or a related subject
  • 4+ years of experience in Data Engineering roles
  • Experience developing sophisticated data pipelines in cloud-based environments (e.g. AWS) using scalable data processing tools (e.g. Apache Spark)
  • Data modeling experience
  • Demonstrated ability to work with others, particularly providing guidance to other data engineers
  • Ability to communicate around complex ideas and topics in English with both technical and non-technical individuals

Responsibilities

  • Design and build reusable and configurable data pipelines using a mix of standard cloud-based and proprietary data platforms
  • Work with a data scientist to develop AI/ML proofs of concept into full implementations
  • Create documentation and provide informal training for data analysts on the configuration and use of tools and pipelines
  • Work with other engineering and product teams to understand proprietary platforms and provide input and feedback
  • Provide guidance to more junior data engineers on best practices
  • Work with security teams to ensure that all servers, platforms, and other resources meet security requirements

Preferred Qualifications

  • Familiarity with Agile methodologies
  • DevOps skills, especially CI/CD experience
  • Configuring and maintaining cloud-based cluster computing resources and orchestration systems (e.g. EC2 instances, Kubernetes clusters, Elastic Beanstalk)

Benefits

Flexible β€œwork from anywhere” policy

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