DataOps Python Engineer for Life Sciences AI

Elsevier; Cambridge; On-site; GBP 60,000 - 90,000; Full time

Job summary

Elsevier's SciBite team in Cambridge is building data and ontology pipelines and AI/NLP technologies to empower life science researchers. As a DataOps Engineer, you will maintain and enhance data and ontology pipelines, collaborating with Ontology and Data Science teams to deliver high-quality vocabularies and data products.

You will develop automation and software to improve efficiency, support customer outcomes, and contribute to continuous DataOps tooling improvement, with AWS Batch, Step

Qualifications

• Experience in Python software development.
• Experience with pytest or unittest and code reviews.
• Proficiency with UNIX and command-line environments.
• Experience using version control systems, ideally GitHub.
• Experience with cloud technologies such as AWS, GCP, or Azure.
• Excellent teamwork and problem-solving skills.
• Experience working in production environments.
• Experience with cloud orchestration tools such as Puppet or Terraform.
• Experience in Python GUI development.
• Experience working with ontologies or XML.

Responsibilities

• Maintain and develop critical ontology import pipelines.
• Support the Ontology Team in updating and building new vocabularies and ontologies.
• Provide support for customer projects as required.
• Develop software to assist manual curation efforts.
• Develop and maintain automation pipelines across the DataOps team.
• Work with AWS Batch, Step Functions, and Lambda-based solutions.
• Collaborate closely with Data Science and Ontology teams.
• Contribute to the continuous improvement of DataOps processes and tooling.

Skills

Python development

UNIX/CLI

GitHub

AWS/GCP/Azure

Testing (pytest/unittest)

Production environments

Terraform/Puppet

XML/ontologies

Compute clusters/workflow

Python GUI development

Tools

GitHub

Terraform

Puppet

Job description

Elsevier's SciBite team in Cambridge is building data and ontology pipelines and AI/NLP technologies to empower life science researchers. As a DataOps Engineer, you will maintain and enhance data and ontology pipelines, collaborating with Ontology and Data Science teams to deliver high-quality vocabularies and data products.

You will develop automation and software to improve efficiency, support customer outcomes, and contribute to continuous DataOps tooling improvement, with AWS Batch, Step