Description
For a major financial institution we are looking for a passionate Scala Dev Engineer
An experienced development engineer who enjoys to work with the latest analytics technology to build APIs that feeds this institutions customers with personal relevant insights and advise. They work with large amount of data, both batch and streaming. The engineers in this area work together with data scientists and data analysts to utilize this data for the benefit of our customers. Their teams are multi-disciplinary and work agile.
Your work environment
You will be part of a team, which consists of engineers who develop software (APIs and end-user applications) that contain sophisticated analytical algorithms, such as machine learning models. Their goal is to be the best team of people that know how to operationalize those algorithms, thereby making predictive analytics and Real Time streaming a reality in application for their customers.
Job description
You are an ambitious, enthusiastic software engineer. You enjoy designing, developing, testing and maintaining complex data-driven systems. Preferably, you have worked with low-latency distributed systems before, or you have read about them and tried some things out for yourself.
You are a good programmer with a strong theoretical basis; nobody has to explain you the details of KISS, DRY, YAGNI and the GoF OOP design patterns. You have some experience in functional programming and know its core principles. You are able to write clean, correct, efficient and maintainable code.
Required skill set:
- REST Api
- Scala
- Akka
- Python
- Cassandra
- Kafka
- Spark/Flink
- Interest for Frontend technologies
- Docker/Kubernetes/Openshift
Do you recognize yourself in this profile:
- Bachelor/Master's degree in Computer Science or related subject
- Knowledge of data manipulation and transformation, eg SQL
- Strong programming skills in Scala with passion for FP. Thrive on challenges around microservices, performance, scalability and concurrency
- Hands-on experience managing and further developing distributed systems and clusters for both batch as well as streaming data (Hadoop/Spark and/or Kafka/Flink)
- Experience in setting up both SQL as well as noSQL databases
- Deployment and provisioning automation tools eg Docker, Kubernetes, Openshift, CI/CD
- Bash Scripting and Linux systems administration
- Security, authentication and authorization (LDAP/Kerberos/PAM)
- Affinity with Predictive Analytics and Machine Learning