Anaconda Enterprise Engineer / Python Engineer (m/f)

AI overview

Support the data science infrastructure by developing Python libraries, administering Anaconda Enterprise environments, and collaborating with multidisciplinary teams on automation and performance.

We are currently looking for a skilled Python Engineer with strong experience in Anaconda Enterprise to join one of our client’s projects. You will play a key role in developing tools and supporting the data science infrastructure, ensuring performance, scalability, and smooth operations across environments used by data teams.

THE WORK:

  • Design, develop, and maintain Python libraries and APIs using FastAPI, Flask, or Django.
  • Administer and support Anaconda Enterprise environments, including user and permission management, environment customization, and platform optimization.
  • Support the integration of packages and dependencies required for data science and machine learning workflows.
  • Implement and maintain infrastructure automation using Terraform, and CI/CD pipelines in Azure DevOps.
  • Monitor system performance, diagnose platform-related issues, and ensure platform responsiveness and reliability.
  • Work closely with data scientists, DevOps, and infrastructure teams to align the platform with user needs and security requirements.
  • Contribute to continuous improvements in reliability, scalability, and user experience of the platform.

Onsite at client site: This role requires an onsite presence with our clients and partners to support project delivery and strengthen client relationships. Our roles require in-person time to encourage collaboration, learning, and relationship-building with clients, colleagues, and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.

HERE’S WHAT YOU’LL NEED:

  • Solid experience in Python development and ecosystem.
  • Proficiency with Python frameworks such as FastAPI, Flask, or Django.
  • Hands-on experience with Anaconda Enterprise or similar platforms used in data science environments.
  • Familiarity with package management tools (e.g., Conda).
  • Strong understanding of cloud platforms, preferably Azure.
  • Experience with Infrastructure as Code (Terraform) and CI/CD pipelines.
  • Knowledge of data science libraries (e.g., pandas, NumPy, SciPy).
  • Understanding of container technologies like Docker and Kubernetes.
  • Strong problem-solving mindset and ability to work across multidisciplinary teams.

As part of our security and compliance procedures, candidates will be required to undergo a criminal background check prior to employment.

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