GeoPhy is a technology company in the real estate space. We provide property valuations engineered for the modern world, giving property lenders and investors fast, consistent and reliable access to information. Our technology allows our customers to understand value and its drivers by using both traditional and unconventional sources, using machine learning to create the most accurate valuations in the market.
GeoPhy’s multidisciplinary teams consist of data scientists, engineers, statisticians and economists, using data science and supervised machine learning to optimize the unprecedented volume and variety of data now available in the real estate sector.
At GeoPhy we consider data being in motion at all times: new data comes in, existing data gets updated or corrected, and any new datapoint might affect hundreds of others. To accommodate this we are building our in-house data management platform, capable of ingesting, integrating, and enriching data on millions of buildings a day. We handle ingestion, management, and also deliver that data to the rest of the business. Our architecture is built around Kafka, and we develop in Scala. Our components and services interact with relational and graph databases as well as ontologies. We run all of this in Kubernetes.
This is an opportunity to work on a one-of-a-kind platform sitting at the very heart of our business.
What you'll be responsible for
- Helping our team build GeoPhy's data platform; this includes engineering, testing, deployment, and maintenance of software components written in Scala.
- Contributing to system architecture design and documentation.
- Managing your own (as well as the team's) priorities, deadlines, and deliverables.
What we're looking for
- Passion for writing high-quality, rock-solid software.
- Appreciation for testing (unit, integration) and automation.
- Knowledge of reactive architecture and microservices.
- Willingness to work with Agile methodologies.
- Excellent communication skills in verbal and written English.
- BS/MSc degree in Computer Science or equivalent practical experience.
Bonus points for
- Production experience with stream-processing architectures built on Kafka.
- Akka expertise.
- Distributed systems.
- Machine Learning engineering.
- Graph databasesSemantic Web (RDF, SPARQL, OWL).
What's in it for you?
- The opportunity to accelerate our rapidly growing organization.
- We're a lean team, so your impact will be felt immediately.
- A Personal learning budget.
- Agile working environment with flexible working hours and location.
- No annual leave allowance; take time off whenever you need.
- Diversity, inclusion, and a zero-tolerance policy towards discrimination.
- A family and pet friendly company.
- Board games, books, and lego.