Senior Data Platform Engineer – Scale, Governance & CI/CD

Senior Data Platform Engineer – Scale, Governance & CI/CD

Full-Time 63000 - 77000 Β£ / year (est.) Home office (partial)
McKesson

At a Glance

  • Tasks: Build scalable data pipelines and enhance platform standards for reliability and security.
  • Company: Join McKesson, a leader in healthcare technology with a focus on innovation.
  • Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Mentor junior engineers and thrive in a dynamic, supportive environment.
  • Why this job: Make a real impact on data governance while collaborating globally with diverse teams.
  • Qualifications: Experience in data engineering, proficiency in Snowflake, dbt, Airflow, and Python.

The predicted salary is between 63000 - 77000 Β£ per year.

Mc Kesson is seeking a Senior Data Engineer to own the Clarus ONE data platform.

You will build scalable data pipelines using Snowflake, dbt, Airflow, and Python, while raising platform standards for reliability, security, and performance.

You will ensure data lineage and governance are embedded, collaborate with Analytics, Data Science, Software Engineering and IT, and mentor junior engineers.

Hybrid UK role with two onsite days, global collaboration, and strong stakeholder communication.

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Senior Data Platform Engineer – Scale, Governance & CI/CD employer: McKesson

McKesson is an excellent employer that fosters a collaborative work culture, encouraging innovation and impactful contributions within the pharmaceutical industry. Located in Greater London, employees benefit from a vibrant city atmosphere, professional growth opportunities, and a commitment to developing strategic partnerships that drive success. With a focus on employee development and a supportive environment, McKesson stands out as a rewarding place to advance your career.

McKesson

Contact Details:

McKesson Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Senior Data Platform Engineer – Scale, Governance & CI/CD

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like McKesson!

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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Platform Engineer – Scale, Governance & CI/CD at McKesson.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like McKesson.

✨Apply Directly through Our Website

When you find a suitable opening like Senior Data Platform Engineer – Scale, Governance & CI/CD at McKesson, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Data Platform Engineer – Scale, Governance & CI/CD

Python
SQL
Problem-Solving Skills
Data Engineering
Data Pipeline Development
API Integration
Communication Skills

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 McKesson, 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 McKesson. 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 McKesson

✨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 McKesson!

✨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.