Insights & Data- BI Architect

Insights & Data- BI Architect

eTeam Workforce Pte Ltd
10-12 years
Not Specified

Job Description


Job Description
  • Primary Responsibilities
    • Solutions
      • Develop/refine Insights & Data architecture for the client covering the complete range from Data Integration/Ingestion till Data visualization. This should be done across a range of technologies including Traditional RDBMS, S/4HANA, SAP BW, SAP BO, QlickView, Informatica, and advanced analytics including Big Data platforms, Data Science/analytics modeling platforms such as SAS, R etc.
      • Craft the appropriate solutions for client's business needs after careful evaluation of options, develop proposals to illustrate business value provided by the technical solutions.
      • Work with the technical SME's to various aspects of the proposal including, software and hardware BOM.
      • Use various industry tools and methods to estimate the scope of work.
      • Resource loading and Financial modeling for the deals.
    • Business Development
      • Own and execute the end to end presentations with customers. This may involve proactive pitches and proposal defense.
      • Collaborate with business stakeholders (customers), vendors, industry consultants and internal(company) SMEs to define information needs, develop business cases and reference architectures.
      • Create and maintain productive relationships with vendors and consultants to resolve operational issues, execute approved initiatives, secure input and counsel on new initiatives, and liaise with software vendors wherever needed.
    • Delivery
      • On a need basis participate in delivery for a short period in order to kick start complex engagements.
      • Assist Project Managers by providing inputs on architecture/technical activities, detail the technical activities and help manage the work packages with the consultants
  • Secondary Responsibilities
    • Guides and up-skills junior analysts, including occasional review of their output.
  • Basic Qualifications
    • Experience and or ability in creating data architectures on both traditional and cloud platforms.
    • Solution experience should span across the entire spectrum of Business Intelligence from ETL to Visualization.
    • The ideal candidate is pro-active, shows an ability to see the big picture and can prioritize the right work items in order to optimize the overall team output.
  • Experience
    • 10-12 years of experience Business Intelligence, Data Warehousing preferably on some or other the Big Data Platform. Must have delivered projects with Data Visualization best practices with traditional and emerging BI tools.
    • Credible experience in architecting, designing and delivering at least one complex EDW and BI engagement is a must.
    • Must be aware of various cloud offerings in the BI landscape like Azure data factory, Amazon EMR, Azure Client workbench etc.
    • Meet with/present to C-Level and prepare with thoroughness for each customer interaction to capably react to unexpected client requirement and leverage your broad experience to help ensure the long-term success of our top tier customers
    • Knowledge of various offerings in the storage or processing stages of BI on cloud platform is a must.
    • Understanding of various tools and technologies in the Visualization layer of the BI stack.
    • Understanding of AI/Client/DL concepts. Experience in any technologies in this space will be added advantage.
    • Should have experience in building or managing data products
    • Should have worked in Agile environments and exposure to DataOps
  • Primary Traits
    • Excellent understanding of BI and EDWH concepts like ETL, Data Quality, Data Governance, Metadata Management, Data Migration, Change Data Capture etc.
    • In-depth understanding of how structured and unstructured data is stored and can be processed.
    • Certification in one of the big data technologies.
    • Experienced in any of the visualization tools such as Tableau / Power BI/QlikSense/Cognos.
  • Secondary Traits
    • Knowledge on various Data Science tools and technologies like R, Python etc
    • Knowledge and understanding of how data science concepts like Data Preparation, supervised and unsupervised learning

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