DataOps Engineer: Python Pipelines & Ontologies

Elsevier Inc.; Soham; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

Elsevier's SciBite team is seeking a DataOps Engineer to maintain and enhance data and ontology pipelines, collaborating with Ontology and Data Science to build vocabularies and data products, and to automate processes that boost efficiency and customer outcomes.

You will work with AWS Batch, Step Functions, and Lambda-based solutions, support production environments, and contribute to continuous improvement of DataOps tooling while promoting a healthy work/life balance and flexible working

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 working 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.
• Knowledge of compute clusters and workflow management.

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

Pytest

UNIX

GitHub

Cloud platforms

Teamwork

Production experience

Terraform

Puppet

XML

Tools

Terraform

Puppet

GitHub

Job description

Elsevier's SciBite team is seeking a DataOps Engineer to maintain and enhance data and ontology pipelines, collaborating with Ontology and Data Science to build vocabularies and data products, and to automate processes that boost efficiency and customer outcomes.

You will work with AWS Batch, Step Functions, and Lambda-based solutions, support production environments, and contribute to continuous improvement of DataOps tooling while promoting a healthy work/life balance and flexible working