Staff Data Engineer and Team Lead

GlaxoSmithKline
London
2 months ago
Applications closed

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Staff Data Engineer and Team Lead

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

Data Engineering is responsible for the design, delivery, support, and maintenance of industrialised automated end to end data services and pipelines. They apply standardised data models and mapping to ensure data is accessible for end users in end-to-end user tools through use of APIs. They define and embed best practices and ensure compliance with Quality Management practices and alignment to automated data governance. They also acquire and process internal and external, structure and unstructured data in line with Product requirements.

This role is responsible for building and leading a scrum team of world-class data engineers focused on building automated, scalable, and sustainable pipelines to account for evolving scientific needs. They support the head of Data Engineering in building a strong culture of accountability and ownership in their team, as well as instilling best-in-class engineering practices (e.g., testing, code reviews, DevOps-forward ways of working). They work in close partnership with our Platforms teams to ensure we have the right tools and ways of working, and with our Bioinformatics teams to ensure the use of appropriate schemas, vocabularies, and ontologies.

Key Responsibilities:

  • Lead a team of data engineers in delivering data and knowledge products that advance GSK R&D

  • Architect of the data delivery and operational strategy for their team, who can deconstruct a complex and ambiguous data or knowledge request into a detailed strategy to make decision, anticipates future issues, and drive engineering efficiencies

  • Partners closely with other data engineering leads to conceptualise the design of new data flows aimed at maximising reuse and aligning with an event-driven microservice enable architecture

  • Partner with other Data Engineering leads to architect an engagement model and optimal ways of working with the product management teams

  • Able to design innovative strategy beyond the current enterprise way of working to create a better environment for the end users, and able to construct a coordinated, stepwise plan to bring others along with the change curve

  • Standard bearer for proper ways of working and engineering discipline, including the QMS framework and CI/CD best practices and proactively spearhead improvement within their engineering area

  • Exemplar leaders in their field of technical knowledge, keen on bettering their understanding and acting as the knowledge holder for the organisation

Why You!

We are looking for professionals with these required skills to achieve our goals:

  • Bachelors’ degree, Data Engineering, Computer Science, Software Engineering, or related discipline

  • Strong data engineering experience in industry

  • Software engineering experience

  • Experience leading a matrix data engineering team

  • Demonstrable experience overcoming high volume, high compute challenges.

  • Familiarity with orchestrating tooling

  • Cloud experience (e.g., AWS, Google Cloud, Azure, Kubernetes)

  • Experience in automated testing and design

  • Experience with DevOps-forward ways of working

  • Deep experience with common big data tools (e.g., Spark, Kafka, Storm, …)

  • Application experience of CI/CD implementations using git and a common CI/CD stack (e.g., Jenkins, CircleCI, GitLab, Azure DevOps)

  • Experience with agile software development environments fluency

  • Experience with Infrastructure as a Code and automation tools (i.e. Terraform)

  • Expertise in data modelling, database concepts and SQL

Preferred:

  • Masters or PhD, Data Engineering, Computer Science, Software Engineering, or related discipline

  • Direct line management of a Data Engineering team

Interested in Joining the Team?

Please apply via our online portal providing your CV and Cover Letter.

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