At a Glance
- Tasks: Lead the design and implementation of CI/CD frameworks for data platforms.
- Company: Join a forward-thinking tech company focused on cloud data solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Be a key player in a dynamic team with significant technical autonomy.
- Why this job: Shape engineering standards and tackle complex challenges in a modern data environment.
- Qualifications: Expertise in Python, SQL, and experience with cloud data platforms.
The predicted salary is between 60000 - 80000 £ per year.
We're looking for a Principal Data Engineer to help define and scale engineering practices across a modern cloud data platform. This is a hands-on technical leadership role focused on platform reliability, automation, CI/CD, testing, observability, and data quality. You'll work across engineering teams to improve how data products are built, deployed, and operated in production while driving engineering standards across a large-scale data ecosystem.
What You'll Be Doing
- Design and implement CI/CD frameworks for data pipelines and analytics workloads
- Drive platform reliability, observability, monitoring, and operational excellence
- Establish automated testing and deployment standards
- Implement Infrastructure as Code and engineering automation practices
- Improve scalability, resilience, and production readiness across data platforms
- Define reusable frameworks, tooling, and engineering patterns
- Champion software engineering best practices across data and AI workloads
- Act as a senior technical leader influencing architecture and platform strategy
What We're Looking For
- Strong experience building and operating modern cloud data platforms
- Expertise in Python and SQL
- Experience with CI/CD, Infrastructure as Code, and platform automation
- Strong understanding of observability, monitoring, testing, and reliability engineering
- Experience working with large-scale data processing and analytics environments
- Ability to operate as both a hands-on engineer and technical leader
Why Apply?
- Principal-level ownership and influence
- Opportunity to shape engineering standards and platform strategy
- Complex platform engineering challenges at scale
- Modern data and AI environment
- High-impact role with significant technical autonomy
Principal Data Engineer employer: Harrington Starr
Join a forward-thinking company that values innovation and technical excellence, offering a dynamic work culture where your contributions as a Principal Data Engineer will directly shape the future of our cloud data platform. With a strong emphasis on professional growth, you'll have access to cutting-edge projects and the opportunity to lead engineering practices that enhance platform reliability and automation. Located in a vibrant tech hub, we provide a collaborative environment that fosters creativity and encourages continuous learning, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Data Engineer
✨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 Harrington Starr!
✨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 at Harrington Starr.
✨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 Harrington Starr.
✨Apply Directly through Our Website
When you find a suitable opening like Principal Data Engineer at Harrington Starr, 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 Principal Data Engineer
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 Harrington Starr, 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 Harrington Starr. 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 Harrington Starr
✨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 Harrington Starr!
✨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.
