Data Quality Engineer
Founded over 10 years ago, Paradine is powering towards our mission of becoming the global leader in sports betting and trading technology. Our team consists of some of the best and brightest minds in data analysis, outcome predictions and trading execution.
We pride ourselves on our ability to consistently innovate and excel in one of the most dynamic and fast-paced markets in the world. We’re on an exciting journey to continue to scale and reveal the immense potential of our business, our world-leading technology sits at the heart of this.
Paradine operates in an industry where access to high-quality information is key. As we grow, we strive to maximise the quantity, range, detail and accuracy of the data that we use. This creates new challenges around our data management operations that require ingenuity, innovation and dedicated resource to solve. You will be a driving force in meeting these challenges, pushing the overall quality of our data ever higher.
To support these efforts we provide an environment where time is dedicated to problem solving and discussion, and give you the opportunity to work with and learn from a group of exceptionally talented people.
As a Data Quality Engineer, you will be central to the design and evolution of Paradine’s data management processes, which provide the Quant team with the high-quality data they need to create profitable models of real-world events. You will work closely with colleagues from both the software development and quantitative teams to understand their challenges and collaborate to drive innovative and compelling solutions to enhance our capabilities.
Working closely with Quant and Development teams in a cross-functional capacity, you will be focussed on ensuring data from multiple sources, internal and external, is clean, validated, mapped and of extremely high quality, ready to be used for modelling.
This role involves software development as well as domain-specific knowledge, as the Data Quality Engineer will be involved in developing robust software solutions to ensure that the data is sound from a sports perspective.
As the main authority in data at Paradine, the Data Quality Engineer will have the latitude and autonomy to build data quality pipelines to meet the needs of the Quant team and integrate with existing solutions provided by the Development team.
- Build, maintain and deploy our data quality and validation pipelines
- Develop and extend data validation and reconciliation checks
- Develop and improve interfaces to expose the data quality status to end-users
- Monitor data on an ongoing basis and liaise with the relevant data sources to fix issues
- Ensure quality of codebase is maintained and improved and follow best development practices
- A degree in a STEM subject or equivalent software development experience
- 3+ years Python experience
- Experience with numpy and pandas
- Experience working on a data quality pipeline
- Experience with git and Linux
- A proactive mentality and an eye for detail
- A strong communicator able to work cross-functionally and explain complex problems and decisions to key stakeholders
Useful but not essential
- Experience with MongoDB and SQL databases
- Experience with docker images for deployment
- Experience with slack integrations
- An interest in sports
Achieving our individual and shared ambitions is built on a variety of unique needs. To support these, Paradine provides a benefits package with flexibility and control to support you.
- Bonus scheme tied to personal and company performance
- Flexible/Remote Work (with a WFH equipment budget)
- Comprehensive Private Medical Insurance (PMI)
- 32 days holiday (including bank holidays)
- 3 extra days to fulfil personal ambitions (learning, volunteering, expeditions,)
- Personal (non-professional) development/learning budget of £250 per year
- Personal wellbeing budget of £100 per month (eg. add family to PMI, wellbeing
- treatments, personal fitness)
- Life Insurance (4x salary)
- Income Protection (75% to SPA)
- Monthly socials and quarterly company events