Oracle ERP Cloud Data Analyst

Overview

On Site
Contract - W2
Contract - 8 day((s))

Skills

Agile
Tableau
Oracle Cloud
Oracle ERP
Financials
Procurement
HCM
OTBI
BI Publisher
Smart View
Power BI
Business Analytics

Job Details

ey Responsibilities: Data Collection & Reporting
  • Extract and prepare data from Oracle Cloud ERP (Financials, Procurement, HCM, etc.) and custom applications for analysis and reporting.
  • Build and maintain dashboards and reports using BI tools like Tableau, Power BI, and OTBI.
  • Validate data accuracy and integrity across data sources, identifying anomalies and gaps.
Analytics & Insights
  • Analyze ERP usage trends, application performance, and business process outcomes to identify opportunities for improvement.
  • Perform root cause analysis for data quality issues, system errors, and business process inefficiencies.
  • Contribute to the design and execution of A/B tests and user behavior analysis to improve app features.
Collaboration & Support
  • Work closely with application developers, product owners, and business teams to define data needs and deliver insights.
  • Support reporting requirements for audits, compliance, and operational planning.
  • Communicate analytical findings through visualizations, summaries, and presentations.
Requirements: Experience
  • 2 4 years of experience in a data analyst, business intelligence, or ERP reporting role.
  • Experience working with Oracle Cloud ERP reporting tools (e.g., OTBI, BI Publisher, Smart View).
  • Proficiency in SQL and data visualization using Tableau, Power BI, or similar tools.
  • Familiarity with enterprise application development and Agile project environments is a plus.
Education
  • Bachelor's degree in Business Analytics, Information Systems, Finance, Computer Science, or a related field.
Additional Requirements
  • Strong attention to detail and problem-solving skills.
  • Ability to work independently and as part of a cross-functional team.
  • Excellent communication skills with the ability to explain technical concepts to non-technical users.
  • Comfortable working with large datasets and multiple data sources in cloud environments.
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