• Azure Data Factory • Azure Databricks • Python, Scala, PySpark, Spark • HIVE / HIVE LLAP / HBASE / CosmoDb • Azure Active Directory Domain Services • Apache Ranger / Apache Ambari • Azure Key Vault • Expertise
• Experience with Hadoop and the HDFS Ecosystem • Strong Experience with Apache Spark, Storm, Kafka is a must. • Experience with Python, R, Pig, Hive, Kafka, Knox, Tomcat and Ambari • Experience with MongoDB • A
• Developing the Best practices documentation to the Application Developer partners to educate how to use the Cloudera Services. • install/Configure/Maintain Apache Cloudera tools like Hive, Impala, Sqoop, Flume, Kafka, HBase, SOLR, and File formats like Avro, Parquet.
• Building efficient storage for structured and unstructured data • Transform and aggregate the data using data processor technologies • Developing and deploying distributed computing Big Data applications using Open Source frameworks like Apache Spark, Apex, Flink,
Description & SummaryA career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational
Candidate should be able to: Coordinate Development, Integration, and Production deployments. Optimize Spark code, Impala queries, and Hive partitioning strategy for better scalability, reliability, and performance. Build applications using Maven, SBT and integrated with continuous integration
