Consultant, Tableau

Position Expectations

  • Understanding of statistical analysis methodologies; experience with data analysis and visualization to create business insights 
  • Visualization and storyboarding to generate insights from the given data
  • Identify right metrics, attributes and data granularity required for a given dashboard
  • Identify the suitable graphical element, charts for the right representation of the numbers
  • Gather and document reporting requirements to meet business needs in order to design,
  • implement and test reports and dashboards using the underlying data store(s), data warehouse(s), and data mart(s).
  • Interface with client to understand their problems and work with the delivery team on solutions that address the client needs
  • Strong analytical and problem solving abilities; attention to detail

Qualification & Experience

  • Knowledge of Tableau/ Spotfire/ Qlikview/ SQL/ Teradata mandatory
  • Experience on Tableau Server and Tableau admin
  • Should have at least 1-5 years of hands-on dashoarding and visualization experience on Tableau/Spotfire/ Qlikview
  • Knowledge of SAS/ R/ Python good to have
  • Deep experience with designing and utilizing relational database systems (e.g. MSSQL, PostgreSQL, MySQL) and developing complex SQL queries
  • Knowledge of logical and physical data modeling concepts (relational and dimensional)
  • Information architecture and UI/UX experience is desired
  • Understanding of data integration issues (validation and cleaning)
  • Familiarity with large and complex data and structures
  • Strong performance tuning experience, specifically related to reporting queries
  • Demonstrated business acumen and cross-collaboration capabilities
  • Strong analytical, conceptual, and problem-solving abilities
  • Knowledge of at least a few analytical approaches good to have
  • Demonstrated ability to handle multiple types of data 
  • Impeccable written, verbal, and interpersonal communication skills

Education:Degree with strong academic credentials; quantitative focus preferred (statistics, economics, computer science or related discipline)


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