At a Glance
- Tasks: Build and optimise data services using modern tools like Python, Spark, and Kafka.
- Company: Join GSK, a leader in R&D and digital innovation.
- Benefits: Competitive salary, bonuses, health insurance, and generous leave policies.
- Other info: Dynamic team environment with opportunities for growth and development.
- Why this job: Make a real impact in healthcare by leveraging data to find new medicines.
- Qualifications: 4+ years of data engineering experience or advanced degree with relevant experience.
The predicted salary is between 130050 - 175950 £ per year.
Overview
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 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 the 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.
A Data Engineer II is a technical contributor who can take a well-defined specification for a function, pipeline, service, or other sort of component, devise a technical solution, and deliver it at a high level. They have a strong focus on the operability of their tools and services, and develop, measure, and monitor key metrics for their work to seek opportunities to improve those metrics. They are aware of, and adhere to, best practices for software development in general (and data engineering in particular), including code quality, documentation, DevOps practices, and testing. They ensure the robustness of our services and serve as an escalation point in the operation of existing services, pipelines, and workflows. A Data Engineer II should be deeply familiar with the most common tools (languages, libraries, etc.) in the data space, such as Spark, Kafka, Storm, etc., and aware of the open-source communities that revolve around these tools. They should be constantly seeking feedback and guidance to further develop their technical skills and expertise and should take feedback well from all sources in the name of development.
Key Responsibilities
- Builds modular code/libraries/services/etc. using modern data engineering tools (Python/Spark, Kafka, Storm, …) and orchestration tools (e.g. Google Workflow, Airflow Composer)
- Produces well-engineered software, including appropriate automated test suites and technical documentation
- Develop, measure, and monitor key metrics for all tools and services and consistently seek to iterate on and improve them
- Ensure consistent application of platform abstractions to ensure quality and consistency with respect to logging and lineage
- Fully versed in coding best practices and ways of working, and participates in code reviews and partnering to improve the team’s standards
- Adhere to QMS framework and CI/CD best practices
- Provide L3 support to existing tools/pipelines/services
Basic Qualifications
- 4+ years of data engineering experience with a Bachelor’s degree.
- 2+ years of data engineering experience with a PhD or a Master’s degree.
- Cloud experience (e.g., AWS, Google Cloud, Azure, Kubernetes)
- Experience in automated testing and design
- Experience with DevOps-forward ways of working
Preferred Qualifications
- Software engineering experience
- Demonstrable experience overcoming high volume, high compute challenges
- Familiarity with orchestrating tooling
- Knowledge and use of at least one common programming language: e.g., Python (preferred), Scala, Java, including toolchains for documentation, testing, and operations/observability
- Strong experience with modern software development tools/ways of working (e.g. git/GitHub, DevOps tools, metrics/monitoring, …)
- 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 Jira and Confluence
- Demonstrated experience with common tools and techniques for data engineering (e.g. Spark, Kafka, Storm, …)
- Knowledge of data modeling, database concepts, and SQL
Salary & Benefits
The annual base salary for new hires in this position ranges from $130,050 to $175,950 taking into account a number of factors including work location, the candidate’s skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share-based long-term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and paid caregiver/parental and medical leave.
Equal Opportunity Statement
GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, colour, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class. If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).
Data Engineer II employer: GlaxoSmithKline
GSK is an exceptional employer that fosters a collaborative and innovative work culture, particularly within the Onyx Research Data Platform team. Employees benefit from competitive salaries, comprehensive health care, and generous leave policies, alongside opportunities for professional growth in a cutting-edge environment focused on leveraging data to discover new medicines. With a commitment to diversity and inclusion, GSK ensures that all employees are valued and supported in their career development.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer II
✨Tip Number 1
Network like a pro! Reach out to current employees at GSK or in the data engineering field on LinkedIn. A friendly chat can give you insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those using tools like Python, Spark, or Kafka. This gives you a chance to demonstrate your expertise beyond just words.
✨Tip Number 3
Prepare for the interview by brushing up on common data engineering challenges and solutions. Be ready to discuss how you've tackled high-volume data problems in the past—real examples go a long way!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team.
We think you need these skills to ace Data Engineer II
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience with data engineering tools like Python, Spark, and Kafka. We want to see how your skills align with the role, so don’t hold back on showcasing relevant projects!
Show Off Your Metrics:When detailing your past work, focus on the metrics you’ve developed, measured, and improved. We love seeing how you’ve made an impact, so include specific examples that demonstrate your ability to enhance data services and pipelines.
Keep It Clear and Concise:Your application should be easy to read and straight to the point. Use clear language and bullet points where possible to make it easier for us to spot your key achievements and skills. Remember, clarity is key!
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at GlaxoSmithKline
✨Know Your Tools Inside Out
Make sure you're well-versed in the tools mentioned in the job description, like Spark, Kafka, and Python. Brush up on your knowledge of these technologies and be ready to discuss how you've used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in data engineering and how you overcame them. Use examples that highlight your ability to handle high volume and high compute challenges, as this will resonate with the interviewers.
✨Understand the Bigger Picture
Familiarise yourself with GSK's mission and how the Onyx Research Data Platform fits into it. Being able to articulate how your role as a Data Engineer II contributes to their goals will show that you're not just technically skilled but also aligned with their vision.
✨Emphasise Collaboration and Feedback
Since the role involves working closely with teams and participating in code reviews, be prepared to discuss your experiences in collaborative environments. Highlight how you seek feedback and use it to improve your work, which is crucial for continuous development.
