At iwoca we are dedicated to building the smartest lending platform in the world as we believe that finance should be as simple, seamless and powerful as electricity. We like to use Agile(ish) processes, which means features or projects go live in days or weeks rather than months or years.
We run our Django-powered site on AWS, use asynchronous tools (Twisted, Celery) for time-consuming tasks and scientific libraries (NumPy, Scikit-learn, SciPy, Pandas) for risk aspects. Application orchestration is done with Docker/Terraform/ECS and our monitoring is set up using DataDog/Sentry.
We are looking for someone who has a solid amount of data engineering experience across different environments. Who can advise on and implement data architecture design. Who will collaborate with business users, analysts and data scientists to deliver high-quality reporting products. You’ll have the opportunity to learn lots on the job and develop rapidly within a high performing team of engineers.
- Develop, construct, test and maintain data architectures and pipelines that align with business requirements.
- Identify practical ways to improve data reliability, efficiency and quality.
- Build, maintain, and document reporting tools that support data driven decision-making by business users.
- Liaise with stakeholders in the wider business to help improve data quality, advise on data strategy and help implement ingestion of new data assets from external sources.
- Assist data scientists in systemising data analysis to be deployed into a production environment.
- Work with analysts to streamline and improve operational and developmental access to data.
- Troubleshoot emerging data and operational problems, and be a source of knowledge for end-users on the most appropriate way of using data for their purposes.
- Support your teammates by learning and sharing your knowledge.
- Experience in implementing reliable and performant data architectures, including ETL pipelines, relational databases, and columnar-storage data warehouses.
- Professional experience in data engineering / software development.
- Professional experience or a degree in a quantitative field, such as Mathematics, Physics, Engineering or Computer Sciences.
- Solid understanding of SQL and relational databases (esp. PostgreSQL).
- Comfortable implementing custom (in-house) data solutions where off-the-shelf products are unavailable or unsuitable.