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BigID

Scans, classifies, inventories enterprise data.

DevOps Engineer

DevOps EngineeringConfirmed live in the last 24 hours
Full-timeTel Aviv-Yafo, IsraelNo salary listed

About the Job

Requirements

  • At least 4 years of experience as a DevOps Engineer.
  • Experience with Python, Bash, or Groovy.
  • A solid grasp of the software development life cycle, best practices, and methods across multiple teams, including Agile development, DevOps, continuous integration and continuous delivery, Kubernetes, team leadership, and test automation.
  • Hands-on production experience managing and troubleshooting Kubernetes clusters and cloud-native microservice architectures.
  • Experience using AI agents and modern large language model tools to optimize infrastructure, operations, and developer workflows.
  • Experience with at least one of Jenkins, GitLab CI, or GitHub Actions.
  • Experience with AWS, Terraform, MongoDB, Elasticsearch, Git, Docker, and relational and non-relational databases.
  • Excellent communication skills for documenting and connecting with other groups.
  • Ability to explore and initiate new ideas, think, and learn independently.
  • Fluency in Hebrew and English.
  • Ability to exercise independent judgment with little or no oversight.

Responsibilities

  • Take the continuous integration and continuous delivery process to the next level.
  • Develop and debug on top of Kubernetes infrastructure.
  • Improve cloud-native Terraform modules.
  • Research new technologies and provide overall technical direction for the team.
  • Plan and drive closure of the automation backlog.
  • Communicate with teams across the organization on testing strategy and design.
  • Propose improvements to the testing process to decrease defects found in production.
  • Work closely with R&D teams in an Agile environment.

Desired Qualifications

  • Experience in REST API automation and testing methodologies.

About the Company

BigID

Scans, classifies, inventories enterprise data.

BigID provides a data management and security platform that scans and inventories enterprise data across cloud, on-premises, and other locations. It classifies data by type (unstructured, structured, and semi-structured) and offers a centralized view to monitor privacy and security risks. The platform integrates with a company’s ecosystem to discover data from multiple sources and help reduce data risk and improve security posture. Its edge comes from broad coverage of both cloud and on-premises data with a unified view of data risk, and it is typically offered on a subscription basis with options for custom demos.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$318.1M
Headquarters
New York City, New York
Founded
2016

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