Nasef Khan is a Staff Engineer with 11 years of hands-on experience delivering reliable QA, DevOps, and technical delivery for data and AI-focused teams at QuantumBlack (McKinsey). He progressed through roles from QA Engineer to Staff Engineer, blending deep quality engineering roots with platform and delivery leadership for production ML pipelines. Nasef contributes to open-source tooling like Kedro, improving documentation and CI/CD workflows—an indicator of his focus on reproducible, maintainable data engineering practices. Based in Stony Stratford, he pairs a scientific background (BSc Biology) with practical software craftsmanship, which helps him translate complex technical requirements into testable, auditable systems. Colleagues rely on him to stabilize builds and documentation, quietly enabling smoother deployments and clearer developer onboarding.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Science (BSc) Biology, Bachelor of Science (BSc) Biology at University of Nottingham
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Role in this project:
DevOps Engineer
Contributions:13 releases, 21 commits, 3 pushes in 2 months
Contributions summary:Nasef's contributions primarily focus on setting up and maintaining the project's documentation and build processes. They added and updated a `.readthedocs.yml` file for documentation builds, added Appveyor badges to the README, and updated the version number in the `kedro/__init__.py` file. These changes suggest a focus on improving the project's build, documentation, and continuous integration infrastructure.
Contributions:171 pushes, 1 branch in 10 years 2 months
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Nasef Khan - Staff Engineer at QuantumBlack, AI by McKinsey