At a Glance
- Tasks: Lead the design and delivery of secure, scalable data solutions in hybrid and cloud environments.
- Company: Join Leonardo UK, a leader in innovative data engineering.
- Benefits: Enjoy a competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on mentoring and continuous improvement.
- Why this job: Make a real impact by transforming raw data into actionable insights.
- Qualifications: Experience in data engineering and strong leadership skills required.
The predicted salary is between 80000 - 100000 Β£ per year.
Leonardo UK is seeking a Principal Data Engineer to lead the design and delivery of secure, scalable data solutions across hybrid and cloud environments. You will guide engineering teams through the full data lifecycle, transforming raw data into actionable insight while partnering with stakeholders.
You will mentor junior engineers, manage project tasks, and drive continuous improvement in data platforms, pipelines and tooling, with a strong emphasis on collaboration across cross-functional teams.
Principal Data Engineer β Hybrid Lead, Data & Cloud Scale in Bristol employer: PVH (Tommy Hilfiger/Calvin Klein)
Intapp is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration within the accounting and consulting sectors across EMEA. With a strong commitment to employee growth, Intapp provides ample opportunities for professional development and leadership coaching, ensuring that team members thrive in their careers while contributing to the company's strategic vision. The culture is built on accountability and high performance, making it an ideal place for those looking to make a significant impact in a rapidly evolving industry.
Contact Details:
PVH (Tommy Hilfiger/Calvin Klein) Recruitment Team
StudySmarter Expert Adviceπ€«
We think this is how you could land Principal Data Engineer β Hybrid Lead, Data & Cloud Scale in Bristol
β¨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 PVH (Tommy Hilfiger/Calvin Klein)!
β¨Show Off Your Projects
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 Principal Data Engineer β Hybrid Lead, Data & Cloud Scale at PVH (Tommy Hilfiger/Calvin Klein).
β¨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 PVH (Tommy Hilfiger/Calvin Klein).
β¨Apply Directly through Our Website
When you find a suitable opening like Principal Data Engineer β Hybrid Lead, Data & Cloud Scale at PVH (Tommy Hilfiger/Calvin Klein), make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesnβt love a direct application? Itβs easier than navigating through job boards!
Some tips for your application π«‘
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. Donβt 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 PVH (Tommy Hilfiger/Calvin Klein), 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 youβre 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 PVH (Tommy Hilfiger/Calvin Klein). 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 PVH (Tommy Hilfiger/Calvin Klein)
β¨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!
β¨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, itβll really make us stand out!
β¨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 PVH (Tommy Hilfiger/Calvin Klein)!
β¨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how weβd 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.