At a Glance
- Tasks: Join a dynamic quant team to build and maintain data workflows for sports betting analysis.
- Company: BettingJobs, a growing player in the sports betting industry.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Collaborative Agile environment with a focus on problem-solving and data integrity.
- Why this job: Make an impact by ensuring high-quality data drives innovative modelling and analysis.
- Qualifications: Strong Python and SQL skills, with experience in data engineering and analysis.
The predicted salary is between 50000 - 70000 £ per year.
BettingJobs is seeking a Data Engineer to join a small but growing quant team in the sports betting industry. Working alongside the modelling team, you will be responsible for ensuring they have access to reliable, well‑structured and high‑quality data for research, modelling and analysis. From building robust Python‑based workflows to investigating complex data issues and assessing new data sources, the Data Engineer will be responsible for extracting maximum value from the data.
Responsibilities
- Work day‑to‑day with quant modellers to prepare, refine and maintain datasets used for research, modelling and analysis.
- Investigate data issues affecting modelling outputs, identifying root causes and working with relevant teams to resolve them.
- Build and maintain Python‑based data workflows and pipelines for ingestion, transformation and validation of modelling data.
- Maintain and develop historical data assets, ensuring they remain accurate, accessible and fit for analytical use.
- Work with engineers to improve upstream and downstream data flows, ensuring critical data is captured and processed effectively.
- Ensure data quality and integrity through validation, reconciliation and targeted monitoring across key datasets.
- Expand visibility into data issues by improving checks, alerts and investigative workflows across critical pipelines.
- Define and improve data logic, transformations and assumptions, ensuring they are clearly documented and consistently applied.
- Support data migrations, backfills and structural improvements to improve the reliability of modelling datasets.
- Contribute to tooling and processes that make it easier to explore, prepare and troubleshoot data used by the quant team.
Requirements
- Strong experience in a Quant Data Engineer, Research Data Engineer or similar role working with complex datasets.
- Understanding of the sports betting industry.
- Strong Python skills for data processing, investigation and workflow development.
- Excellent SQL skills and solid experience with relational databases, preferably PostgreSQL.
- Proven experience preparing, transforming and validating datasets for analytical, modelling or research use.
- Experience investigating data issues and tracing problems through pipelines, transformations and source systems.
- Experience building and maintaining data pipelines or processing workflows in production environments.
- Strong understanding of data quality, reconciliation and validation practices.
- Experience working with analytical data warehouse technologies such as ClickHouse, BigQuery, Snowflake or Redshift (beneficial).
- Experience with version control systems (preferably GitLab) and tools such as JIRA and Confluence.
- Comfortable working with messy, incomplete or evolving datasets and turning them into reliable assets.
- Experience working in Agile environments and collaborating with distributed teams.
- Excellent attention to detail, strong problem‑solving ability and clear verbal and written communication skills.
Data Engineer - Quantitative Analysis employer: BettingJobs
BettingJobs offers a dynamic and innovative work environment for Data Engineers, particularly those passionate about the sports betting industry. With a focus on collaboration within a small yet growing quant team, employees benefit from hands-on experience with complex datasets and cutting-edge technologies, alongside opportunities for professional growth and development. The company fosters a culture of continuous improvement and values the contributions of each team member, making it an excellent place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Quantitative Analysis
✨Tip Number 1
Network like a pro! Reach out to folks in the sports betting industry, especially those working as Data Engineers or in quant roles. A casual chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python workflows and data pipelines. This is your chance to demonstrate how you tackle complex datasets and ensure data quality – make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and data validation practices. Be ready to discuss specific challenges you've faced with data issues and how you resolved them. We want to see your problem-solving skills in action!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to get noticed by the hiring team. Plus, we love seeing candidates who are proactive and engaged with our platform.
We think you need these skills to ace Data Engineer - Quantitative Analysis
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 projects in the sports betting industry. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific examples of data pipelines or workflows you've built. If you've tackled complex datasets or resolved tricky data issues, let us know! This will help us understand your hands-on experience.
Be Clear and Concise:When writing your cover letter, keep it clear and to the point. Explain why you're interested in the role and how your background makes you a great fit. We appreciate straightforward communication!
Apply Through Our Website:Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at BettingJobs
✨Know Your Data Inside Out
Before the interview, make sure you’re familiar with the types of datasets you might be working with in the sports betting industry. Brush up on your experience with Python and SQL, and be ready to discuss specific examples where you've transformed or validated data. This will show that you understand the role and can hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to share stories about how you've tackled complex data issues in the past. Think about specific challenges you faced, the steps you took to investigate and resolve them, and the outcomes. This will demonstrate your analytical mindset and ability to work through messy datasets, which is crucial for this role.
✨Familiarise Yourself with Tools and Technologies
Make sure you know the tools mentioned in the job description, like PostgreSQL, ClickHouse, or GitLab. If you have experience with any of these, be ready to discuss it. If not, do a bit of research to understand their functionalities and how they relate to data workflows. This shows your commitment to learning and adapting.
✨Communicate Clearly and Confidently
During the interview, practice clear and concise communication. Be prepared to explain technical concepts in a way that’s easy to understand, especially if you're discussing your work with non-technical team members. Good communication is key in collaborative environments, so highlight your ability to convey complex ideas simply.
