Follow data-access and privacy rules, protect secrets and escalate unsafe AI behavior or data exposure.
Contribute reusable components and improvements to data pipelines and analytical tools.
Take ownership of agreed deliverables and raise issues affecting quality or timelines.
Maintain code quality, maintainability and reliability.
Deliver tested components and support documentation on time.
Recommend implementation options and make code, testing and documentation decisions within agreed standards.
Basic Qualifications
One of the following
Master’s degree; OR
Bachelor’s degree and 2 years of related experience.
Preferred Qualifications
5 to 9 years of experience in Data Engineer
Master’s degree in Computer Science, Data Science, Informatics, Software Engineering, Statistics or another technical discipline.
Internship or early-career experience in the pharmaceutical or high-tech industry.
Strong programming skills in Python and/or R, with familiarity with SQL.
Familiarity with version control, software testing and documentation.
Familiarity with data structures, pipelines, APIs and cloud environments; approved AI integrations where relevant.
Basic ML and generative AI literacy and the ability to learn approved tools with review.
Working knowledge of software design, testing, debugging and maintainable code.
Ability to run specified AI tests and record model, prompt and data versions.
Ability to handle permitted data securely and recognize privacy, access and unsafe-AI-behavior risks.
Learning agility, structured problem-solving, accountability and effective collaboration.
Ability to explain software behavior, data flows and technical issues clearly to the intended audience.
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