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- Tasks: Build and maintain data pipelines for real-time sports betting data.
- Company: Innovative software company in the exciting world of sports betting.
- Benefits: Lucrative salary, bonuses, and excellent benefits package.
- Why this job: Join a talented team and work on cutting-edge data engineering projects.
- Qualifications: 4+ years in data engineering with skills in Python, SQL, and streaming technologies.
- Other info: Dynamic environment with opportunities for growth and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
A Data Engineer is required for an exciting and innovative Software sports betting company based in London. The successful candidate will join a talented horse racing team and will be working closely with the quantitative researchers and alongside other extremely talented and driven engineers to build and support systematic trading models. You will be joining a tight-knit team of research mathematicians, computer scientists and trading analysts at the top of their chosen fields.
You will be building and maintaining data pipelines that ingest data from multiple external providers, APIs, and real-time feeds, designing and implementing streaming data architectures to support low-latency trading requirements.
Responsibilities- Build and maintain data pipelines that ingest data from multiple external providers, APIs, and real-time feeds.
- Design and implement streaming data architectures to support low-latency trading requirements.
- Collaborate with quantitative researchers, computer scientists, and trading analysts as part of a cross-functional team.
- 4+ years of experience in data engineering, with deep experience in Python, SQL, and data modelling.
- Experience with cloud data warehouses, orchestration frameworks, and transformation tools.
- Hands-on experience with streaming technologies (Kafka or similar).
- Experience integrating data from external APIs and third-party providers.
- A degree in Computer Science or a numerical subject.
- Snowflake for data warehousing
- Python 3.12+
- DBT for transformations
- Kafka for streaming
- ClickHouse for real-time analytics
Working alongside other extremely talented and driven engineers. Extremely lucrative salary, bonus and excellent benefits. Greenfield Python/Data engineering work, both challenging and rewarding.
Data Engineer employer: Venture Up
Contact Detail:
Venture Up Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data engineering game. Building relationships can open doors that job applications alone can't.
✨Show Off Your Skills
Don’t just tell them what you can do; show them! Create a portfolio of projects that highlight your experience with Python, SQL, and streaming technologies like Kafka. Having tangible examples of your work can really set you apart from the crowd.
✨Tailor Your Approach
When reaching out to potential employers, make sure to tailor your message to their specific needs. Mention how your skills align with their tech stack and how you can contribute to their team. Personalisation goes a long way!
✨Apply Through Our Website
We’ve got some fantastic opportunities waiting for you on our website. Don’t miss out! Applying directly through us not only shows your interest but also gives you a better chance of getting noticed by our hiring team.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with Python, SQL, and any relevant data modelling skills. We want to see how your background fits with our exciting projects!
Showcase Your Projects: Include specific examples of projects where you've built data pipelines or worked with streaming technologies like Kafka. This helps us understand your hands-on experience and how you can contribute to our team.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon unless it's relevant to the role. Let’s get straight to what makes you a great fit!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to track your application and ensure it reaches the right people in our team!
How to prepare for a job interview at Venture Up
✨Know Your Tech Stack
Make sure you’re well-versed in the core technologies mentioned in the job description, like Python, SQL, and Kafka. Brush up on your knowledge of Snowflake and DBT too, as they might ask you specific questions about how you've used these tools in past projects.
✨Showcase Your Collaboration Skills
Since this role involves working closely with quantitative researchers and other engineers, be prepared to discuss your experience in cross-functional teams. Share examples of how you’ve collaborated on projects, highlighting your communication skills and ability to work towards a common goal.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of data pipelines and streaming architectures. Practice explaining your thought process when designing data solutions, and be ready to solve problems on the spot. This will demonstrate your hands-on experience and problem-solving abilities.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about the team dynamics, the challenges they face with data integration, or how they measure success in their projects. This not only shows your enthusiasm but also helps you gauge if the company is the right fit for you.
