Technical Architect

• MUST HAVE - Python, R, Design and test AI algos, models. 5 year experience in AI modelling
• Cloud Computing: Accenture cloud platform, Amazon Web Services, Azure, GCP Cloud Architecture, Google cloud, IBM Infosphere Information Server, IBM Infosphere Warehouse Edition, Mulesoft CloudHub, Oracle Cloud, Red Hat Cloud
• Data Access Tools: Azure Data Explorer, Azure Stream Analytics, MS SQL Server Management Studio, SQL Developer, TOAD
• Data Modelling Tools: Erwin, Excel, Power Designer, Sparx, Visio
• Distributed Systems: Azure ADLS Gen 2, Databricks, Hadoop, HDFS, Kafka, MapReduce/Hive, Spark, Storm, Zookeeper
• Enterprise Architecture Tools: Spark Enterprise Architect
• Graph Databases: AWS DynamoDB, Azure Cosmos, DataStax Enterprise Graph, IBM Graph, InfiniteGraph, Neo4j, Teradata Aster, Titan
• Hadoop Distributions: Azure Databricks, Cloudera, Hortonworks, MAPR
• In Memory Databases: SAP HANA
• NoSQL Columnar Stores: Accumulo, AWS RedShift, Cassandra, Druid, HBase, Vertica
• NoSQL Document Stores: Apache CouchDB, ArangoDB, Clusterpoint, Couchbase, DocumentDB, Elastics Search, IBM Domino, MarkLogic, MongoDB, OrientDB, Qizx, RethinkDB, Sharepoint
• NoSQL Key Value Pair Data Stores: Aerospike, DovetailDB, Dynamo, Dynomite, Flare, Hyperdex, Keyspace, MotionDb, Oracle NoSQL Database, Quasardb, RAMCloud, Riak, SchemaFree, SubRecord, Voldemort
• Relational MMP Databases: Netezza, Teredata
• Relational SMP Databases: Azure SQL PaaS, IBM DB2, MySQL, Oracle, PostgreSQL, SQL Server

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