Jr. Data Analyst

Imperial DadeJersey City, NJ
2d$52,000 - $56,000

About The Position

Join an ambitious Data & Analytics group, helping to continue to grow and expand this large, Privately Equity owned international Company. Imperial Dade is the leading distributor of foodservice packaging, industrial packaging and facilities maintenance supplies and equipment in the U.S., Puerto Rico, Canada and the Caribbean. As a provider of customized supply chain solutions, the company serves customers in many business-to-business market segments including supermarkets, grocers, healthcare facilities, education, and restaurants. Job Overview: The Data Analyst within the Data & Analytics Group is tasked with optimizing data from 40+ ERP systems leveraging various tools and programming to enable the organization to make faster and more effective data-driven decisions. In addition, the Data Analyst will automate processes as well as design and build new and more advanced data models.

Requirements

  • Bachelor’s Degree in Information Systems, Computer Science, Supply Chain or related field of study
  • Fluency in Microsoft Excel (lookups, formatting, pivots, etc)
  • Problem-solving skills: Able to think quickly and use logic to solve problems
  • Aptitude to learn other technical applications quickly
  • Basic SQL experience

Nice To Haves

  • Power Query (SQL, M, R, Dax) or Power BI a plus
  • Internship experience is a big plus

Responsibilities

  • Collect, transform, and manage large datasets to enable project teams to optimize sourcing across a vast vendor & SKU portfolio of 120 DCs, 1000 suppliers, 100,000 SKUs
  • Cleanse, map and convert data from 40+ ERP systems to standardized formats amidst large variation
  • Validate & aggregate incoming acquisition raw data for onboarding into databases & models
  • Provide gap fill of data across various data table domains to improve data quality
  • Conduct Data extraction from multiple sources for larger D&A project support
  • Enforce MDM best practices across the organization, especially at newly acquired entities
  • Support the integration of analytics models into production workflows
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