Experience with cloud platform technologies Microsoft Azure or AWS
On premises Big Data platforms such as Cloudera, Hortonworks
Big Data Analytic frameworks and query tools such as Spark, Storm, Hive, Impala
Streaming data tools and techniques such as Kafka, AWS Kinesis, Azure Streaming Analytics
ETL (Extract-Transform-Load) tools such as Pentaho or Talend or Informatica); also experience with ELT
Continuous delivery and deployment using Agile Methodologies.
Data Warehouse and DataMart design and implementation
NoSQL environments such as MongoDB, Cassandra
Data modeling of relational and dimensional databases
Metadata management, data lineage, data governance, especially as related to Big Data
Structured, Unstructured, Semi-Structured Data techniques and processes
Machine Learning (R, Scala Python)
Over 10 years of engineering and/or software development experience and demonstrable architectureexperience in a large organization.
Experience should contain 5 years of experience of architecturesupport combined of these environments: data warehouse, data mart, business intelligence, and big data.
5+ years of consulting experiencedesired
Hands-on experience in Big Data Components/Frameworks such as Azure Cortana Analytics Suite, .Net, Hadoop, Spark, Storm, HBase, HDFS, Pig, Hive, Scala, Kafka, .Net, R, Python, PyScripts, Unix Shell scripts
Experience in architecture and implementation of large and highly complex projects
Deep understanding of cloud computing infrastructure and platforms
History of working successfully with cross-functional engineering teams
Demonstrated ability to communicate highly technical concepts in business terms and articulate business value of adopting Big Data technologies