As a Principal Data Engineer you’ll work across these teams and are responsible for making sure they deliver the highest quality data products through the adoption and continuous improvement of patterns and practices, tools and frameworks and processes.
You will work closely with your peers and Engineering Leadership to help shape and refine the software development life cycle; an open-ended tasking which is less about outlining a ‘one size fits all’ approach and more about identifying, nurturing and playing to the strengths of each individual team.
Proven knowledge of the Data Science Life cycle
Demonstrable experience of ANY these software engineering languages Java 8, Scala 10/11, Maven / SBT
R or Python (preferably with pandas, numpy and/or sci-kit learn)
Great understanding of the processes and principles of machine learning system
Sound knowledge of the Apache Big Data stacks such as Hadoop and Spark including, HDFS MapReduce, YARN
Good understanding of real-time streaming technologies such as Apache Kafka, Azure EventHub, Spark Streaming, Apache Storm, Apache Flink etc
Strong knowledge of Microsoft Azure data capabilities (Azure Data Factory, Azure Stream Analytics, SQL DB / DW, CosmosDB, Azure Data Lake etc)
Great understanding of modern data architecture, service-oriented, API based and load leveling application design principles, lambda, streaming and micro-batch architectural knowledge and experience
For more information please email Billy Gavin at firstname.lastname@example.org
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