Senior Data Engineer - Data Quality in London

Senior Data Engineer - Data Quality in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Made Tech

At a Glance

  • Tasks: Develop and maintain high-quality data platforms for public sector organisations.
  • Company: Join Made Tech, a leader in data-driven solutions for the public sector.
  • Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on innovation and collaboration.
  • Why this job: Make a real impact by enabling data-driven decisions in the public sector.
  • Qualifications: Experience in data engineering and a passion for mentoring others.

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

Job Description hackajob is collaborating with Made Tech to connect them with exceptional professionals for this role.

\Our Senior Data Engineers enable public sector organisations to embrace a data-driven approach by providing data platforms and services that are high-quality, cost-efficient, and tailored to clients’ needs.

They develop, operate, and maintain these services.

They make sure they provide maximum value to data consumers, including analysts, scientists, and business stakeholders.

\As a Senior Data Engineer, you may play one or more roles according to our clients' needs.

The role is very hands-on and you'll support as a senior contributor for a project, focusing on both delivering engineering work as well as upskilling members of the client team.

At other points, you might play more of a technical architect role and work with the larger Made Tech team to identify growth opportunities within the

Made Tech

Contact Details:

Made Tech Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Engineer - Data Quality in London

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 Made Tech!

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 - Data Quality at Made Tech.

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 Made Tech.

Apply Directly through Our Website

When you find a suitable opening like Senior Data Engineer - Data Quality at Made Tech, 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 - Data Quality in London

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

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 Made Tech, 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 Made Tech. 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 Made Tech

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 Made Tech!

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.