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Data Engineer – Scala – Spark – Kafka – AWS

Data Engineer – Scala – Spark – Kafka – AWS

Job title Data Engineer – Scala – Spark – Kafka – AWS
Contract type: Permanent
Location London
Industry: Data
Salary: Up to £100,000 (Depending on experience)
Reference: DE-LDN-CB
Contact name: Carl Baird
Contact email: carl.baird@signifytechnology.com
Published: August 2, 2019 10:25

Job Description

Senior Data Engineer – Scala – Spark – Kafka – AWS

 

This role provides the opportunity to work on the following tech stack: Scala, Spark, Kafka, AWS & Docker/Kubernetes.

The company:

This company is evolving alongside personal mobility as more vehicles are fleet-owned and Insurance must adapt to the changing risk profile. Consumer decisions & preferences are forcing underwriting models to be transformed. Increasing usage of technology has created a torrent of new data which enhances the predictive power of modern AI-driven applications. Their core product utilizes streaming telematics data and amends insurance pricing in real-time responding to the drivers' needs, environment, behaviour and usage.

The role:

They have built their working environment around the people and not the skills required (although they are important). They believe heavily in open source software, idea sharing & open collaboration throughout all development teams. They need people who share the same values and know how important they are to the success of the project.

Benefits:

  • Competitive salaries
  • Options scheme and will benefit from being an early joiner
  • Work from the office, from home or anywhere!
  • Very flexible and generous holiday policy
  • Opportunity to learn and develop skills within a modern working environment.

Key Skills:

  • Spark/Flink/Kafka automated testing experience.
  • Scala, Java. Functional programming experience. Python experience a plus.
  • AWS frameworks.
  • Kubernetes/Docker – Microservices.
  • Jenkins, Maven or Gradle, Git, Ansible.
  • Prometheus, Grafana.
  • Experience developing or testing microservices, especially data-centric ones.
  • Interest in systems architecture and building distributed systems at scale.
  • Strong automation mindset and a passion for root cause analysis.
  • Expertise in performance tuning and service monitoring.

Nice to haves:

  • Event sourcing / CQRS patterns
  • Timeseries data stores (Influx DC, CrateDB)
  • NoSQL databases (Cassandra or HBase)
  • Modern data warehousing (Hive, Kylin or Presto)
  • Indexing and search engines (Elasticsearch)

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