Data Engineer: AI Pipelines & Data Quality (Equity, Hybrid London) in England

Data Engineer: AI Pipelines & Data Quality (Equity, Hybrid London) in England

England Full-Time 60000 - 70000 £ / year (est.) Home office (partial)
SENZO

At a Glance

  • Tasks: Build and maintain data pipelines for product and analytics.
  • Company: Mission-driven tech company in London with a focus on innovation.
  • Benefits: Competitive salary, equity, and hybrid work model.
  • Other info: Great opportunity for career growth in a dynamic environment.
  • Why this job: Join a team driving AI initiatives and make a real impact.
  • Qualifications: Strong in Python and SQL; AWS experience is a plus.

The predicted salary is between 60000 - 70000 £ per year.

A mission-driven technology company in London is looking for an Entry-level Data Engineer to build and maintain data pipelines that aid product and analytics.

This role involves integrating data sources into a reliable data layer, ensuring quality checks, and supporting future AI initiatives.

Candidates should be strong in Python and SQL, ideally with experience in AWS.

Competitive salary of £60,000 - £70,000 plus equity, and hybrid work model offered.
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Data Engineer: AI Pipelines & Data Quality (Equity, Hybrid London) in England employer: SENZO

Join a mission-driven technology company in London that prioritises innovation and employee growth. With a competitive salary and equity options, you will thrive in a hybrid work environment that fosters collaboration and creativity. Our supportive culture encourages continuous learning and development, making it an excellent place for aspiring Data Engineers to launch their careers.

SENZO

Contact Details:

SENZO Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer: AI Pipelines & Data Quality (Equity, Hybrid London) in England

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 SENZO!

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 Data Engineer: AI Pipelines & Data Quality (Equity, Hybrid London) at SENZO.

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 SENZO.

Apply Directly through Our Website

When you find a suitable opening like Data Engineer: AI Pipelines & Data Quality (Equity, Hybrid London) at SENZO, 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 Data Engineer: AI Pipelines & Data Quality (Equity, Hybrid London) in England

Python
Problem-Solving Skills
SQL
Data Engineering
Communication Skills
Data Quality Assurance
Data Pipeline Development

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 SENZO, 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 SENZO. 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 SENZO

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 SENZO!

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.