Senior Data Engineer β€” Cloud, Streaming & Platform Scale

Senior Data Engineer β€” Cloud, Streaming & Platform Scale

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
Harnham

At a Glance

  • Tasks: Design and build high-volume data pipelines in a modern cloud environment.
  • Company: Harnham, a leader in data engineering and analytics.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Join a dynamic team and make a real impact in the data space.
  • Why this job: Lead exciting migration projects and optimise environments for analytics and ML.
  • Qualifications: Strong experience with streaming data, cloud platforms, and mentoring skills.

The predicted salary is between 60000 - 80000 Β£ per year.

Harnham is seeking an experienced Senior Data Engineer to design, build and operate high-volume data pipelines in a modern cloud environment.

You will lead complex migration projects and optimise lakehouse environments to support analytics, ML and data science initiatives.

The role requires strong experience with streaming data solutions, cloud platforms, Kubernetes and Ia C, plus the ability to mentor engineers and coordinate with data scientists and business stakeholders.

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Senior Data Engineer β€” Cloud, Streaming & Platform Scale employer: Harnham

Join a leading UK-based media organisation at the forefront of digital transformation, where your role as Director of Streaming Product and Growth will be pivotal in shaping the future of their subscription services. With a strong emphasis on innovation and a collaborative work culture, you'll have access to significant growth opportunities, competitive salary packages, and a performance-based bonus structure, all while working in a dynamic environment that values data-driven decision making and customer-centric strategies.

Harnham

Contact Details:

Harnham Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Senior Data Engineer β€” Cloud, Streaming & Platform Scale

✨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 Harnham!

✨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 Senior Data Engineer β€” Cloud, Streaming & Platform Scale at Harnham.

✨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 Harnham.

✨Apply Directly through Our Website

When you find a suitable opening like Senior Data Engineer β€” Cloud, Streaming & Platform Scale at Harnham, 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 Engineer β€” Cloud, Streaming & Platform Scale

Data Pipeline Design
Cloud Platforms
Streaming Data Solutions
Kubernetes
Infrastructure as Code (IaC)
Mentoring Skills
Collaboration with Data Scientists

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 Harnham, 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 Harnham. 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 Harnham

✨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 Harnham!

✨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.