Posts List

Data Engineering Manager at the leading data-driven travel Advertising platform at travel audience GmbH (Berlin, Germany)

Job description As a part of Strategic Growth Businesses (SGB) unit of Amadeus, Travel Audience is the world’s leading data-driven travel advertising platform. The business unit harnesses the power of cutting edge machine learning practices to connect the leading performance-oriented advertisers with the biggest network of publishers, reaching millions of travellers. The strategy is to optimize advertising across the entire traveller journey, identify and create new audiences, and increase our partners reach, relevance and booking volumes.

Be a Big Data Engineer (m/f/o) in our team of awesome professionals at COYO GmbH (Hamburg, Deutschland)

Data Engineer (m/f/o) You are a problem solver (m/f/o), detail-oriented and self-motivated who thrives in a fast-paced, highly dynamic environment, combining technical, product, business and leadership perspectives. Area: Business Intelligence Start: April 2019 Location: Hamburg What we are looking for: You are a team player (m/w/o)You have a hands-on mentality and you are into Big Data.You have experience in working with programming languages like Scala, SQL, Python, R, Java.You know Spark, Streaming Libraries, Hadoop Ecosystems (Hive, HDFS, YARN, etc.

Be a Data Engineer (m/f/o) in our team of awesome professionals at COYO GmbH (Hamburg, Deutschland)

Data Engineer (m/f/o) You are a problem solver (m/f/o), detail-oriented and self-motivated who thrives in a fast-paced, highly dynamic environment, combining technical, product, business and leadership perspectives. Area: Business Intelligence Start: April 2019 Location: Hamburg What we are looking for: Your are a team player (m/w/o)You are experience in either Scala, Python or JavaYou know Spark, Streaming Libraries (Spark Streaming, Kafka Streams, etc.), Hadoop Ecosystem (Hive, HDFS, YARN, etc.)You have prior experience with RDBMS and NoSQL databases and as a result know which storage type to use for a particular use-cases, how to create a good data model and write efficient SQL for future extractionsHands-on experience with BigQuery would be a great plusYou previously worked with mature CI/CD pipeline and made several production deployments during the dayWhat you will do: