Business Intelligence Engineer

2 weeks ago


Andover, United States Mastech Digital Full time

Requirement Description:

  • Mine, manipulate, and analyze data from multiple internal and external sources, reporting key actionable insights using statistical rigor to inform the larger organization of noteworthy trends that impact the business.
  • Develop deep-dive tools, UIs, metrics, and QuickSight automated dashboards to give visibility into key measures of logistics performance.
  • Partner with the Product, Finance, Logistics, Clinical, and Tech teams to gather requirements, create reporting, and drive analytic projects that help solving complex logistics challenges.
  • Constantly investigate and support implementation of new big data technologies to provide automated solutions to address the evolving Transplant Logistics needs.
  • Support the ongoing design of the NOP logistics network.


Background and Qualifications:

  • 5+ years of professional experience.
  • Advanced SQL skills and experience in scripting for automation (e.g., Python).
  • Experience programming to extract, transform, and clean large (multi-TB) datasets.
  • Experience building KPIs and developing automated dashboards and reporting solutions.
  • Experience with data visualization using Tableau, Power BI, QuickSight, Smartsheet, and other similar tools.
  • Expert level Excel skills, including knowledge of VBA, Macros, Pivot Charts, and Statistical Modeling.
  • Knowledge of data modeling, machine learning, relational databases, Python, and Geospacial data processing.
  • Experience working directly with business stakeholders, being able to seamlessly navigate between data and business needs.
  • Self-starter, driver, and out-of-the-box thinker with a strong attention to detail and comfortable with ambiguity.
  • "Can do" attitude, willingness to roll up sleeves up with a drive to win.
  • Ability to work independently with minimal supervision and collaborate with teammates and cross-functional colleagues.
  • Strong business ethics.


Education:

  • BS in computer science, engineering, economics, math, or related field.
  • Master's degree in statistics, data science, or an equivalent quantitative field is a highly valued.



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