The Smarkets exchange is a multi-billion pound trading platform with a rapidly growing ecosystem of sophisticated users who apply financial trading techniques to the world of betting. We’re creating a data engineering function, so this is the perfect time to join and be there at the beginning!
Understanding how our users operate requires us to unlock more insights in the data. Whether it's to protect the exchange, understand the dynamics of event trading for capacity planning, or make historical trading data available for analysis, improving the usability and accessibility of our exchange data is key to our continued growth. We have generated terabytes of data from multiple sources in an interesting and challenging domain, however in order to apply this data to more challenges we need tooling to sample, combine and extract data from our Redshift and BigQuery databases.
What you’ll be doing:
- You’ll architect the data pipelines that hook into the exchange, and build the tooling to help others gain the insights they need
- Using Postgres, Kafka, Amazon Redshift, Google BigQuery and Luigi (not Mario, sadly) on a daily basis
- Collaborating with data scientists and engineers across Smarkets
- Working on improving the collection, processing, storage and dissemination of our data across the company
Engineers at Smarkets:
- Proactively evolve things across the company and positively contribute to the engineering culture by sharing knowledge and discussing solutions with colleagues
- Advocate for code quality. We all believe in the power of code reviews, test driven development, continuous delivery (we deploy to production several times a day) and most importantly, we’re interested in continuously improving
- Define their role in the context of self management (we’ll help you with this)
You’ll be an experienced data engineer with a passion for creating reliable and deterministic data pipeline infrastructure. You are passionate about data engineering, and have deep, proven experience in it. More specifically:
- You’ll have dealt with with big data volumes (of at least a few Terabytes) and have a great track record of building automated, scalable and robust data processing systems
- You have a good understanding of database technologies and you know the practical and theoretical difficulties of building distributed systems
- Experience with data warehouse systems like BigQuery, Redshift or Presto and both batch and semi-online building blocks like MapReduce, Spark, Kinesis, dataflow etc.
- Experience in managing financial time series
- Knowledge of statistics, data science, machine learning or scientific computing
- Interest in sports betting or trading
- To help you keep your money, we also chip into your pension and feed you three fantastic, freshly prepared meals every day
- Room for you to do things your way
- Uncapped holiday - you take a break when you need it, as long as you don’t leave your team in the lurch!
- A lovely, tranquil office to work in - right in the heart of Saint Katharine Docks
- And yes, we also have the industry standard perks such as a foosball table and massive screens for gaming with your colleagues, team activities and monthly get-togethers - known as “the Expiration party”
Our strength is technology and trading with a passion to push the known boundaries of real-time financial technology. With our self-management structure, flexible work environment and uncapped holiday allowance, Smarkets offers a unique opportunity to be part of a great work culture. Our office in St Katharine’s Docks (Tower Hill) comes complete with a fantastic roof terrace and a team of in-house chefs cooking breakfast and lunch every day. Food is big at Smarkets, and lunch al’desko is officially banned.
The fine print:
The salary range for this role is from £70,000-£115,000 and also includes stock options, plus other benefits listed above. Your salary will be determined by peer review and we’ll have open discussions with you about this. We are committed to pay parity and unlike a lot of other companies, we disclose salary information internally.
We transfer and store the information you submit to help us process your application and to make our hiring process better. We also make use of third-party hiring tools to help us process applications. As we are based in both Europe and the United States, your data may leave the European Economic Area when we process it. Please only submit your application if you are happy for us to use your information in this way.