Xanadu is an innovative technology company that develops best-in-class betting software and provides operational support and services for clients in Europe and in the US. Our largest client is Matchbook, one of the world's leading and most sophisticated betting exchanges.
Matchbook is no ordinary website, it has more in common with the New York Stock Exchange than with a bookmaker. It operates at a massive scale, processing more than 500 million API requests a day with an average response time of under 50ms, while also handling billions of dollar’s worth of transactions. To put some of this into perspective, Matchbook processes more transactions each day than Amazon.com does on Black Friday.
With more regulated markets opening in the US and around the world we face new opportunities for further expansion, leveraging our cutting-edge technology to provide our partners with an extremely performant and dependable exchange system.
We are looking for a talented Data Engineer to join our Data Analytics function. If you bring an enthusiasm to all things data related and working with technologies such as Python, Airflow, Spark, Greenplum, Docker excites you then please get in touch with us as we’d love to hear from you.
What will I be doing?
- Collaborating with product and analytics engineers on the build-out of new data pipelines using both internal and third party data sources
- Contributing to the build-out of new workflow processes and associated monitoring and alerting
- Data integrity promotion and development of automated quality assurance tests
- Providing assistance in the ongoing management of our data platform
- Identifying and promoting efficiencies and increasing reliability at all stages of data pipelines
- Troubleshooting production issues, identify and implement effective solutions
- Providing support to Product Engineering and overall development of data assets
- Contributing to schema design, data consistency and the company data dictionary;
- Helping deliver overall company data governance and compliance
- Promotion of data-driven decision making as part of the overall company culture.
What are we looking for?
- Undergraduate and/or postgraduate degree in a STEM field
- Experience creating ETL processes
- Fluency in writing SQL and experience with at least one NoSQL database
- Experience with open source languages such as Python/Spark/Scala/R
- Familiarity with data engineering tools and proficiency with at least one: Airflow/Luigi, ElasticSearch, Cassandra
- Experience using Linux as a development environment
- Strong data science experience and knowledge of data modelling approaches
- Be a team player capable of conducting independent research
- Have a high level of attention to detail
- Experience with unit testing
- Experience with good code management practices (Git)
- Familiarity with visualization software and techniques (Qlikview or Tableau)
- Familiarity with CRM software such as Salesforce
- At least a year industry experience