Data Analyst II — Power BI & Supply Chain Analytics

Ryder System, Inc.

Concord (NH)

Remote

USD 65,000 - 90,000

Full time

3 days ago
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Benefits offered by this job

Health benefits (medical, dental, etc)
401(k) plan
Paid time off

Job summary

Ryder System, Inc. is seeking a Data Analyst II to deliver final business solutions via Power BI experiences for the operations team.

You will shape data into clear, actionable visuals and become a domain expert in supply chains, leveraging Ryder's Azure Data Lake to drive analytics initiatives. You will design dashboards and reports, collaborate with data analysts and scientists, and push the boundaries of big data, including streaming data into the data lake and experimenting in the data

Qualifications

  • Bachelor's degree in Supply Chain, Data Analytics or equivalent.
  • Master's degree preferred in Supply Chain, Data Analytics, MBA or equivalent.
  • Two (2) years or more Applied Projects experience: digital transformation, data management in educational/project or intern environment.

Responsibilities

  • Develop Dashboards by understanding business needs and translate data into usable visualizations to drive decisions.
  • Engage the business to evaluate needs and prioritise ad-hoc requests.
  • Know Ryder Business and the supply chain ecosystem and data role within it.
  • Enhance data maturity and integration to standardize core functionality and enable multiplier effects.
  • Perform other duties as assigned.

Skills

Power BI
Tableau
SQL
ETL tools
-.NET

Education

Bachelor's degree in Supply Chain, Data Analytics or equivalent
Master's degree preferred

Tools

Alteryx
SSIS

Job description

Ryder System, Inc. is seeking a Data Analyst II to deliver final business solutions via Power BI experiences for the operations team.

You will shape data into clear, actionable visuals and become a domain expert in supply chains, leveraging Ryder's Azure Data Lake to drive analytics initiatives. You will design dashboards and reports, collaborate with data analysts and scientists, and push the boundaries of big data, including streaming data into the data lake and experimenting in the data

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