Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Create and maintain data pipelines to support business functions and analytics.
- Company: Join McKesson, a leader in the pharmaceutical supply chain.
- Benefits: Competitive salary, health benefits, and opportunities for innovation.
- Other info: Collaborative environment with a focus on cutting-edge cloud technologies.
- Why this job: Make a real impact on healthcare by optimising data infrastructure.
- Qualifications: 3+ years in a data role, strong SQL and Python skills required.
The predicted salary is between 50000 - 65000 £ per year.
McKesson’s Corporate is seeking a Data Engineer in Greater London to create and maintain data pipelines supporting various business functions. The role involves monitoring the production environment and working closely with analytics and data science teams to ensure an efficient data infrastructure.
Candidates should have at least 3 years of experience in a data-centric role, strong coding skills in SQL and Python, and experience with cloud-based data technologies like Snowflake. This position supports innovation in the pharmaceutical supply chain.
Data Engineer: Build Scalable Pipelines & Analytics in London employer: McKesson’s Corporate
Contact Detail:
McKesson’s Corporate Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer: Build Scalable Pipelines & Analytics in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at McKesson on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data pipelines and analytics projects. We want to see how you’ve tackled real-world problems using SQL, Python, and cloud tech.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on coding challenges related to data engineering. We can help you find resources to sharpen those skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have tips and updates on the hiring process right there.
We think you need these skills to ace Data Engineer: Build Scalable Pipelines & Analytics in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data-centric roles, especially with SQL and Python. We want to see how your skills align with the job description, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our innovative work in the pharmaceutical supply chain. Keep it concise but impactful!
Showcase Your Technical Skills: Since we’re looking for someone with strong coding skills and experience with cloud-based technologies like Snowflake, make sure to include specific examples of your work with these tools. We love seeing real-world applications of your skills!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at McKesson’s Corporate
✨Know Your Data Tools
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss specific projects where you've used these languages, especially in building data pipelines or working with cloud technologies like Snowflake.
✨Understand the Business Context
Familiarise yourself with McKesson’s role in the pharmaceutical supply chain. Knowing how data engineering supports various business functions will help you demonstrate your understanding of the bigger picture during the interview.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and coding abilities. Practice coding challenges related to data engineering, and be prepared to explain your thought process clearly.
✨Show Your Collaborative Spirit
Since the role involves working closely with analytics and data science teams, be ready to share examples of how you've successfully collaborated in the past. Highlight your communication skills and how you’ve contributed to team success.