At a Glance
- Tasks: Lead a team of data engineers to deliver innovative data solutions for GSK's R&D.
- Company: Join GSK, a global biopharma leader dedicated to advancing health through science and technology.
- Benefits: Enjoy competitive salary, bonuses, health insurance, retirement plans, and generous leave policies.
- Other info: Be part of a diverse team committed to creating a workplace where everyone can thrive.
- Why this job: Make a real impact on healthcare by leveraging data to discover new medicines.
- Qualifications: Bachelor's degree in Data Engineering or related field with 7+ years of experience.
The predicted salary is between 80000 - 100000 £ per year.
At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines. 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, metadata- and automation-driven 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, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time
Data Engineering is responsible for the design, delivery, support, and maintenance of industrialized automated end-to-end data services and pipelines. They apply standardized 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, structured 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 decisions, anticipate future issues, and drive engineering efficiencies.
- Partners closely with other data engineering leads to conceptualize the design of new data flows aimed at maximizing reuse and aligning with an event-driven microservice-enabled 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 organization.
Basic Qualifications:
- Bachelors degree in Data Engineering, Computer Science, or Software Engineering
- 7+ years of professional experience
- Software engineering experience
- Cloud experience
- Experience in automated testing and design
Preferred Qualifications:
- Masters or PhD
- Strong data engineering experience in industry
- Demonstrable experience overcoming high volume, high compute challenges
- Familiarity with orchestrating tooling
- Experience with DevOps-forward ways of working
- Deep knowledge and use of at least one common programming language: e.g., Python, Scala, Java
- Deep experience with common big data tools (e.g., Spark, Kafka, Storm, ...)
- Cloud experience (e.g., AWS, Google Cloud, Azure, Kubernetes)
- 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 using tools like Jira and Confluence
GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organization where people can thrive. Getting ahead means preventing disease as well as treating it, and we aim to positively impact the health of 2.5 billion people by the end of 2030. Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a workplace where everyone can feel a sense of belonging and thrive as set out in our Equal and Inclusive Treatment of Employees policy. We’re committed to being more proactive at all levels so that our workforce reflects the communities we work and hire in, and our GSK leadership reflects our GSK workforce.
Staff Data Engineer and Team Lead employer: Gsk
At GSK, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to thrive. As a Staff Data Engineer and Team Lead, you will lead a talented team in a cutting-edge environment focused on innovation and collaboration, with ample opportunities for professional growth and development. Our comprehensive benefits package, commitment to diversity, and mission-driven approach to healthcare make GSK an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Data Engineer and Team Lead
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Staff Data Engineer and Team Lead
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Gsk, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Gsk. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Gsk
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Gsk!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.