Data Engineer (Relocation to Munich, Germany)

Our client is the leading guest feedback platform in the world. Their goal is to improve the travelling process from finding the best hotel to spending the best stay. So, the company collaborates with hotels and travel websites all over the world. The system analyzes hundreds of millions of travels reviews and transforms it into data visualizations for hotels all over the world.  

You’re supposed to be a part of a great international team with experience in machine learning, natural language processing and big data technologies. We’re looking for the person who is keen on researching, prototyping and finetuning algorithms to solve novel problems to join the team. The team will encourage you to take on responsibility.

 

   What will you do?

    • Being a member of a cross-discipline delivery team;
    • Work with raw data at scale using Hadoop MR and Spark;
    • Make optimizations and improvements of existing features or data processes for performance and stability;
    • Use machine learning algorithms to improve the product;
    • Work with hundreds of GB of data processing pipelines.

   What do we expect from you?

    • Experience as Data Engineer (3+years);
    • Very strong Python;
    • Experience in Java and Scala;
    • You’re not just a good developer, you’re an architect;
    • Experience in creating data pipelines and ETLs using MapReduce, Spark or Flink.

   Will be great if you have experience with:

    • Pandas, Scikit-learn, Scipy, Luigi / Airflow;
    • Linux scripting;
    • Big Data technologies (Hadoop, Spark, Flink, Hive, Impala, HBase, Pig, Redshift, Kafka);
    • REST-APIs using Python;
    • Data Mining, machine learning, natural language processing or information retrieval;
    • AWS or another cloud;
    • Agile (Scrum or Kanban.

   What do we offer?

    • Flexible hours;
    • Learning development;
    • Free snacks, fruit and drinks;
    • Team breakfast;
    • Beer O’clock;
    • Foreign languages classes;
    • Team events;
    • Sport groups;
    • Adventure days.
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