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Data(Ops) Engineer (m/f)

  • Job type: Permanent
  • Location: Hamburg
  • Salary: Competitive
  • Job reference: MJ-BigData-515190
  • Sector: BI & Big Data, Glocomms
  • Date posted: 05/02/2018
Data(Ops) Engineer (m/f)
Hamburg



The company wants to reimagine how small businesses utilize technology. They have built an open business platform to develop solutions that help 200+million small businesses stay competitive in a connected world. Efficiencies and scalability that are typically only available to large enterprises. 

As a Data(Ops) Engineer (m/f) you will join an experienced and international engineering team who values and practices transparency, supportive feedback, and direct communication.



Your role

This role is to ensure an uninterrupted flow of data between servers and applications. You would be responsible for data architecture. Design, construct, install, test and main high scalable data management systems. This is a DevOps role with a bit more Dev than Ops. While DevOps combines the development and operations teams, DataOps is the set of best practices that improve coordination between machine learning engineers and operations 
  • Design, develop and deliver scalable, high-performance services for our world-changing products. 
  • You enjoy working with globally distributed, loosely coupled systems in the cloud. 
  • Curious about emerging trends and quickly evaluate and adapt to new technologies. 
  • Work in a full-stack development environment on a small agile team. 
  • You are self-driven and highly motivated to deliver top-tier solutions with minimal guidance. 


Skills

You have worked extensively in a number of programming languages, but are partial to Python or Scala. Git and continuous integration are part of an everyday workflow, and you are not a stranger to automation/configuration management tools like Ansible. 
  • Hadoop, Apache Spark, Apache Kafka, Apache Mesos, Microservice Data Processing. 
  • In-depth experience with Python, Scala or Java.
  • DevOps Ansible, Docker.
  • Architecture.
  • AWS Cloud.
  • 60% Software Engineering / 40% Infrastructure/Operations. 
  • M.Sc. Computer Science or related field. 
  • Familiar working with AWS environments. 
  • Expert in Cassandra, Elasticsearch, MongoDB or SMACK stack.
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