Job Location: IL - Chicago
Regional Description: Midwest
Job Number: 00660035 00660035_en
Big Data Architect, with expertise in solutions for processing large volumes of data, using tools ETL, BI and Big Data platforms. Proven experience of at least 2-3 years in architecture and development of different processes around Big Data platforms. Hadoop Distribution: Hadoop HortonWorks - Hands–on experience in Big Data solutions (Hadoop Ecosystem) ETLs and Data Marts. - NoSQL platforms: MongoDB, Cassandra, ElasticSearch, Redshift - Cloud services: familiarity with Amazon/Azure cloud - Hadoop Framework Experience: Hive, Kerberos, HDFS, Kafka, Spark, will be valued. Knowledge and experience working with ETL solutions - Talend, Asterix - Understanding of cluster and parallel architecture as well as high-scale or distributed RDBMS, SQL experience and No_SQL platforms - Understanding of major programming/scripting languages like Java, Linux, PHP, Ruby, Python and/or R Also valuable: - Real-Time analytics and BI platforms such as Tableau Software - Statistical software packages such as R, SPSS, MatLab, … - Solid IT consulting experience in data stores and large scale implementations Other professional skills: - To be able to work in teams with different disciplines - To be a self-managed person - To be able to work in a agile development environments - To be able to perform detailed analysis of business problems and use designing in Big Data solutions - To be able to work creatively in a problem-solving environment - To be able to do the analysis, processing and visualization of data for processing large volumes of data
Data as a Service (DaaS) is part of Enterprise Insight Platform - a shared big data analytics platform. The objective of DaaS is to bring people closer to the data - data scientists, business analysts, developers, and data owners. Big data engineer will translate logs and data from various data ingestion, storage, and viz applications to present in a front end tool. Source applications include: HDFS, Hive, EBI, Talend, Spark. Given the constant flux of the big data analytics market, new tools will likely be introduced so the ability and enthusiasm for new technology is also important.
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