Data Architect AI

Design and test AI algos, models.  3-5 year experience in AI modelling  

Data architect should have experience in structured & unstructured data management, and AI/ML data store design.  Asst Dir preferred.

Skills and attributes for success

  • Solution Architecture & Design – Capability to help clients design solution architecture & requirements for feeding into package definition, solution build, etc. Includes technical system architecture, logical data models, networking models, hardware architecture & requirements. Architectures include: Conceptual IS service, Logical application, Physical application, Conceptual data, Logical data, Physical data, Conceptual platform services, Logical technology, Physical technology, Security, Transition, Architecture roadmap.
  • Data Architecture and Design – Capability to define the models and standards by which data is sourced, stored, distributed and governed within an organization
  • Enterprise Content Management – Capability to define solutions that will catalog, organize and store an organization’s internal unstructured information, e.g. word documents, emails etc.
  • Master, Reference and Metadata Management – Capabilities to develop solutions that define the master data (internal glossary of key data items), the reference data (external glossary of standard data items and values) and metadata (the data that describes the data set)
  • Vendor Package and Partner Selection – Capability to identify software packages and solutions that could meet client solution requirements and develop requests for proposal (RFPs) from these vendors. Assist clients in the evaluation of the resulting proposals, including the package capabilities and fit to the requirements (business and technology), vendor proposals for pricing and support

To qualify for the role you must have

  • 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
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