Amsterdam - Netherlands - Meetings will be based in Amsterdam
Around 7 months Freelance ZZP
Our current vision and aspiration is to decompose the service and migrate it to a cloud (AWS) infrastructure. It will isolate the business domains and drive the ownership of our functionality which should result in reducing time to market for launching new products and supporting existing ones, in addition to strengthening the reliability of the service.
Important Aspects Of The Job Include
Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.
Solving issues with data and data pipelines, prioritising based on customer impact.
End-to-end ownership of data quality in our core datasets and data pipelines.
Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.
Providing tools that enhance Data Quality company-wide.
Providing self-organising tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.
We are looking for a Data Engineer who enjoys solving problems, who initiates solutions and discussions and who believes that any challenge can be scaled with the right mindset and tools.
We have found that people who match the following requirements are the ones who fit us best:
Minimum of 3 years of experience in the field, using 2 or more server-side programming languages -- preferably Java, Scala, Python, Perl, etc.
Experience with building scalable data pipelines in distributed environments with technologies such as Hadoop, Cassandra, Kafka, Spark, HBase, MySQL, etc.
Knowledgeable about data modelling, data access, and data storage techniques.
Understands and can develop streaming processing applications using technologies like Flink, Kafka-Streams, Spark-Streaming, etc.
Hands-on experience of developing in and contributing to open-source data technologies, such as Hadoop.
Demonstrable experience with SQL, HQL, CQL, etc.
Experience of working on systems on a large scale.
Good understanding of basic analytics and machine learning concepts.
Preferably a university degree in Computer Science.