Power BI Lead (CPG) Job at Tiger Analytics, Dallas, TX

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  • Tiger Analytics
  • Dallas, TX

Job Description

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges. We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.

We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector and we are beefing up our talent in the space.

We are looking for someone with a good blend of business consulting skills and a data analytics background to add to our team.

Requirements

  • Bachelor's degree in Computer Science or related field
  • 10+ years of experience in a Business Intelligence space
  • Knowledge of Power BI Business intelligence reporting tool is a must
  • Knowledge of SQL is a must
  • Deep knowledge and understanding of the CPG space in Sales, marketing and Supply chain.
  • Experience and knowledge with Data Warehouse ETL process using SSIS packages is preferred
  • Ability to engage with executive/VP-level stakeholders from the client’s team to translate business problems into high-level analytics solution approaches.
  • Consulting experience is highly preferred

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