Data & Analytics Technical Architect

Sandy Springs, GA | Contract To Hire

Post Date: 08/08/2017 Job ID: 46524 Industry: Architect

Data & Analytics Technical Architect

Summary:

The Data & Analytics Technical Architect has a broad knowledge of data ingest and load scenarios and is an expert at transforming business requirements into the supporting dimensional models, reporting experience while meeting data refresh service level agreements.  With an understanding of both Big Data and traditional architectures the Architect will lead delivery teams implementing these solutions in the cloud and in on-premise environments.  It is also expected that the Architect understand machine learning techniques and processes to support Data Scientists that may be on the team.

Responsibilities:
  • Works with product team to understand project requirements
  • Build reusable code and libraries for future use
  • Ensure the technical feasibility of design team outputs
  • Optimize application for maximum speed and scalability
  • Assure that all user input is validated before submitting to back-end
  • Develop new and effective interactive design solutions on time and in scope
  • Collaborate with Data Scientist team to deliver on new business initiatives and platform enhancements

Requirements:
  • A strong understanding of dimensional modelling techniques
    • Transactional, periodic, and accumulating fact table design patterns
    • Additive and semi-additive measures.  MDX or DAX expressions is a plus
    • Slowly changing dimension principals and design
    • ETL, partitioning, and change data capture load techniques
    • The ability to design dimensional models that best lend themselves to a particular report type.
  • A functional understanding of big data technologies
    • Specific knowledge of the Hadoop ecosystem and how the various programs support big data movement and analytic
    • Practical experience with at least one major distribution, i.e., Cloudera, Hortonworks, Microsoft HDInsight, etc.
    • An understanding of how big data and traditional BI solutions integrate and some of the common concerns that should be addressed
  • A high-level understanding of Machine Learning
    • Major algorithm classes and training needs, e.g., supervised versus unsupervised
    • ML process understanding, such as CRISP-DM
  • An understanding of the data analytics technology landscape and vendor offerings with additional depth in the Microsoft stack
    • Azure based analytics tools including Stream Insights, Azure Data Warehouse, Azure Analysis Services, Azure Data Factory, Azure Data Lake, Microsoft R Server, Azure ML, Power BI, and SQL Server technologies
  • An understanding of the collaboration technology landscape
    • Microsoft Office 365 and associated applications
    • SharePoint 2013, 2016, and SharePoint Online capabilities matrix and a high-level understanding of the product roadmap
    • An understanding on how Power BI and other analytics technologies compliment Office 365 and on-premise collaboration
    • An understanding of hybrid collaboration topologies
  • The ability to explain the Scrum development process and how team members contribute to this methodology
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