Data Operations Engineer - London, United Kingdom - GlaxoSmithKline

Description

Site Name:
London The Stanley Building

The Onyx Research Data Platform organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines.

We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward:

Building a next-generation data experience for GSK's scientists, engineers, and decision-makers, increasing productivity and reducing time spent on "data mechanics"
Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent
Aggressively engineering our data at scale to unlock the value of our combined data assets and predictions in real-time
We are looking for a skilled Data Operations Engineer I to join our growing team.

The DataOps team accelerates biomedical and scientific data product development and ensures consistent, professional-grade operations for the Data Science and Engineering organization by building templated projects (code repository plus DevOps pipelines) for various Data Science/Data Engineering architecture patterns in the challenging biomedical data space.

A Data Operations Engineer I knows the metrics desired for their tools and services and iterates to deliver and improve on those metrics in an agile fashion.

A Data Operations Engineer I is a technical contributor who can take a well-defined specification for a function, pipeline, service, or other sort of component, and a technical approach to building it, and deliver it at a high level.

They are aware of, and adhere to, best practice for software development in general (and their specialization in particular), including code quality, documentation, DevOps practices, and testing.

A Data Operations Engineer I should have awareness of the most common tools (languages, libraries, etc) within their specialization.

A Data Operations Engineer I is a technical individual contributor, building modern, cloud-native systems for standardizing and templatizing data engineering:

Develop and support delivery of high-performing, high-impact data ops products and services, from a loosely defined data engineering problem or requirement.

Produces well-engineered software, including appropriate automated test suites and technical documentation.
Ensure consistent application of platform abstractions to ensure quality and consistency with respect to logging and lineage.
Stayup-to-datewith developments in the open source community aroundDevOps,data engineering, data science, and similar tooling.
Bachelor's degree in computer science, Software Engineering, or related discipline
Experience using at least one common programming language (e.g., Python, Scala, Java), including toolchains for documentation and testing.
Experience with Infrastructure/Configuration as Code tools and techniques (e.
Experience in modern software development tools / ways of working (e.g. git/GitHub, devops tools, ...)
Master's or PhD in computer science, Software Engineering, or related discipline.
Exposure to tools, techniques, etc relevant to their specialization area (e.g. building data Platforms, data Engineering and Operations)
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