DataOps Python Engineer — Flexible Hours, High Impact

Elsevier; Cambridge; Remote; GBP 60,000 - 90,000; Full time

Benefits offered by this job

Flexible working hours

Wellbeing initiatives

Study assistance

Sabbaticals

Job summary

Elsevier in Cambridge is seeking a Python Software Engineer to help build and evolve data and ontology solutions powering scientific technologies. You will contribute to data pipelines, automation, and tooling across the DataOps stack, collaborating with Ontology and Data Science teams.

The role requires Python expertise, experience with UNIX, GitHub, and cloud services, plus a track record in production environments. We offer flexible working patterns and a supportive environment.

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.
• Experience with cloud orchestration tools such as Puppet or Terraform.
• Experience in Python GUI development.
• Experience working with ontologies or XML.
• Knowledge of compute clusters and workflow management.

Responsibilities

• Maintain and develop critical ontology import pipelines.
• Support the Ontology Team in updating 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 with Data Science and Ontology teams.
• Contribute to the continuous improvement of DataOps processes and tooling.

Skills

Python

pytest/unittest

UNIX/CLI

GitHub

AWS/GCP/Azure

Puppet/Terraform

Python GUI

XML/ontologies

Production systems

Teamwork

Tools

GitHub

Terraform

Puppet

AWS Batch/Step Functions/Lambda

Job description

Elsevier in Cambridge is seeking a Python Software Engineer to help build and evolve data and ontology solutions powering scientific technologies. You will contribute to data pipelines, automation, and tooling across the DataOps stack, collaborating with Ontology and Data Science teams.

The role requires Python expertise, experience with UNIX, GitHub, and cloud services, plus a track record in production environments. We offer flexible working patterns and a supportive environment.