Rugsusa

Rugsusa

Data Analytics Engineer

New York, NY · Full-time

Sponsorship not specifiedDetected 6 days ago
SQLSnowflakeCI/CDdbtData AnalysisData EngineeringWireframingCommunication

About the role

  • Follow development standards in accordance with UA best practices.

Responsibilities

  • Position Overview The Data Analytics Enginee r designs, builds, and supports RugsUSA's enterprise data warehouse and business intelligence platform.
  • The role also supports ongoing platform performance, data quality, and self-service analytics across the organization.
  • Interact with internal stakeholders to gather/develop functional and technical requirements and translate them into reporting solutions.
  • Model, design, develop, test and implement the appropriate backend and front-end structures needed to meet business visualization and reporting requirements.
  • Build aggregate data models.
  • Manage the data flow to reflect in dashboards to meet business requirements.
  • Build dimension views and fact tables.
  • Data formatting and processing to build the foundation layer for dashboards and self-service reporting.
  • Manage the steady state data warehouse and BI output Responsible for the full life cycle of development, from requirements gathering through data transformation coding and report/dashboard design and creation.
  • Responsible for daily support of the data warehouse and associated data marts.

Requirements

  • Build dashboards as required to follow wireframes designs, integrate with backend data models.
  • You Have Bachelor's degree in Computer Science, Computer Engineering, Information Systems or related technical field.

Skills

  • Work on data transformation, using the ELT tools.

Company info

  • About RugsUSA Since launching in 1998, Rugs USA has established itself as a leading innovative online destination for an extensive variety of high-quality, on-trend area rugs at prices customers won't find anywhere else.

This listing is sourced directly from Rugsusa's careers page and normalized into a canonical job model.