At a Glance
- Tasks: Build dashboards and ensure data quality for a cutting-edge trading platform.
- Company: Dynamic London trading scale-up focused on crypto markets.
- Benefits: Competitive salary, hands-on experience, and a small team environment.
- Other info: Work in a collaborative office with direct ownership from day one.
- Why this job: Join a fast-paced team and make a real impact on market data integrity.
- Qualifications: Strong Python skills, dashboard building experience, and knowledge of data pipelines.
The predicted salary is between 80000 - 80000 £ per year.
Data Quality Engineer| £80,000 | London | Trading Scale Up | Python, SQL, Type Script
Crypto markets move at machine speed. Somebody has to make sure the data isn't lying to us.
I'm recruiting for a London capital markets firm built for the onchain world.
They're making waves with an already impressive team and are looking for someone to own the visualization and observability of the market data platform.
They run their own proprietary trading infrastructure, and the market data it produces is good enough that institutional clients now pay for it directly.
It's grown into its own product, and they're pushing further.
They just picked up rights to distribute a major prediction markets data feed.
They're after a Data Quality Engineer, and this one's a strong fit if you've written proper Python, built dashboards, and spent real time in and around data pipelines.
What you'll actually be doing
- Building dashboards across live exchange feeds, historical datasets, venue health, latency and gaps, using Python and Type Script.
- Writing the checks and pipeline logic that catch problems in data before a client ever sees them.
- Defining what "good data" really means, not just whether a job ran, but whether the numbers coming out the other end hold up.
- Reconciling order books, trades, funding rates and derivatives across CEX and DEX venues.
- Working closely with engineers to trace issues back through the pipeline to their root cause, not just patch the symptom.
What they're looking for
Strong hands-on Python, comfortable writing real production code, not just scripts.
Experience building dashboards, in Python or Type Script, that people actually used to understand what was going on.
Solid working knowledge of data pipelines, how they're built, where they break, and how to instrument them properly.
2+ years somewhere the output genuinely mattered, data quality, data engineering, or similar.
A real eye for data that's subtly wrong, not just loudly broken.
- Must be in commutable distance of their London office
- Must have Full right to work in the UK
- London, in office, on purpose. Small team, no layers, real ownership from day one
- #J-18808-Ljbffr
Data Quality Engineer in London employer: Avetix
Join a dynamic trading scale-up in London where your expertise as a Data Quality Engineer will directly impact the integrity of market data. With a strong emphasis on collaboration and ownership, you'll thrive in a culture that values innovation and precision, while enjoying opportunities for professional growth in a fast-paced environment. The company's commitment to cutting-edge technology and a supportive team atmosphere makes it an exceptional place for those looking to make a meaningful contribution in the capital markets sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Quality Engineer 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 Avetix!
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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 Avetix.
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We think you need these skills to ace Data Quality Engineer in London
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 Avetix, 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 Avetix. 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 Avetix
✨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 Avetix!
✨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.
