Cloud and Data Developer
3 weeks ago
What You Will Do:
- Engage in hands-on development work to achieve objectives outlined by product/service owners.
- Review and process structured datasets for database insertion and GUI integration.
- Develop and refine QA processes for databases and dataset releases.
- Enhance and test GUI and search interface capabilities linked to datasets.
- Support the Health Data Standards Branch in promoting health data standards and terminologies.
- Assist in digital repository migration and data transformation for the NLM Digital Collections team.
- Provide enhanced support for the development of USCD web resources.
- Participate in the development, testing, and refinement of GUI enhancements and search interface capabilities tied to underlying datasets.
- Support digital repository migration and data transformation of binary files (video, audio, images, PDF) and associated metadata to a system ready for content ingests.
- The Developer will collaborate with other NLM teams, including the Security Team and other Contractors, as needed.
What You Will Need:
- Master’s degree in Computer Science, Engineering, or a related field
- Experience with Elastic Search, Postgres, and Solr implementation/debugging.
- Proficiency in application development using Docker Containers and using GitLab, Bamboo, and other CI/CD pipeline tools.
- Skills in Java, Python/Django, JavaScript, CSS, Ruby, HTML5, and Oracle or Postgres SQL.
- NonSQL database management experience, preferably in MongoDB or Cassandra with the ability to share, define schema, etc., as well as supported tools like NodeJS and AngularJS
- Strong grasp of computer science principles, such as data structures and algorithms.
- Solid experience in the use of software engineering tools like JIRA, agile methodology, test-driven development, etc.
- Experience in cloud computing environments like AWS, Azure, or Google Cloud.
- Proficient in Agile Method and applying it in software development.
What Would Be Nice To Have:
- Additional certifications or training in AI, machine learning, or data science.
- Familiarity with natural language processing (NLP) and large language models.
- Experience in AI model deployment and monitoring.
- Knowledge of privacy and security considerations in AI applications.
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