Oracle EPM EPBCS Data Integration - AI Agent Specialist
Duration: 12 Months + Extension
Bill Rate: $90/hr
Job Type: W2 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Description :
We are seeking an experienced Oracle EPM EPBCS Data Integration & AI Agent Specialist to support a multi year Finance Transformation initiative. This role will design, build, and optimize enterprise planning data flows, automate close & planning processes using Oracle AI Agents, and ensure seamless integration across ERP, EPM, and analytics platforms.
The ideal candidate brings deep hands on expertise in EPBCS, Data Integration (Data Exchange / Data Management), REST APIs, linux automation, and emerging AI driven automation within Oracle Cloud EPM.
Key Responsibilities
1. EPBCS Application & Model Support
Configure and enhance EPBCS modules (Financials, CapEx, Projects, Assets and Flow Custom Modeling).
Build and maintain data integration across Oracle ERP , Files, and AWS Snowflake data sources
Build data integrations across the EPBCS environment for reporting
Optimize metadata structures integrations with Oracle EDMCS
Build and maintain outbound data flows for downstream systems (Oracle FDI)
2. Data Integration & Automation
Design and manage end to end data pipelines using:
o Data Integration / Data Exchange
o Data Management (FDMEE concepts)
o EPM Automate
o REST API integrations
Build automated workflows for metadata loads, actuals ingestion, forecast refreshes, and scenario rollovers.
Troubleshoot data load issues, mapping logic, and validation rules.
3. AI Agent Enablement (Oracle EPM)
Implement and configure Oracle EPM AI Agents to automate:
o Data validation
o Variance analysis
o Intercompany reconciliation
o Narrative generation
o Close task orchestration
Develop AI driven insights and anomaly detection models to support FP&A and Controller teams.
Partner with Oracle product teams and internal AI architects to leverage new AI capabilities.
4. Finance Transformation Delivery
Work with Finance SMEs to translate planning, forecasting, and consolidation requirements into scalable EPM solutions.
Work with Data SMEs for source to target EPM integrations
Redesign and automate Planning process aligned to :
o Monthly close
o Forecast cycles
o Annual planning
o Long range planning
Ensure alignment with enterprise data governance and reporting standards.
5. Cross Functional Collaboration
Partner with ERP, Data Engineering, Analytics, and Finance teams to ensure consistent data definitions and integration patterns.
Provide technical documentation, knowledge transfer, and training to Finance and IT stakeholders.
Required Qualifications:
5 10+ years of hands on Oracle EPM Cloud experience (EPBCS required).
Strong expertise in Data Integration, Data Exchange, Data Management, and EPM Automate.
Proven experience with REST APIs, scripting, and automation frameworks.
Working knowledge of AI/ML concepts and experience implementing Oracle EPM AI Agents (or similar intelligent automation tools).
Deep understanding of FP&A, financial close, and corporate finance processes.
Ability to translate business requirements into technical solutions with minimal supervision.
Preferred Qualifications:
Experience with FCCS, ARCS, or PCMCS.
Background in Finance, Accounting, or FP&A.
Experience in large scale Finance Transformation or ERP modernization programs.
Familiarity with Snowflake, Oracle OCI , or enterprise data platforms.
Consulting experience with Oracle, Deloitte, PwC, EY, KPMG, or similar.
Soft Skills:
Strong communication and stakeholder management skills.
Ability to work in a fast paced, ambiguous environment.
Proactive problem solver with a continuous improvement mindset.
Comfortable working with senior Finance leadership (CFO, Controller, FP&A Director).
Success Criteria :
Reliable, automated data flows across ERP EPM Reporting.
AI Agents deployed to reduce manual effort in close and planning cycles.
Faster forecast cycles and improved data quality.
High user adoption and strong partnership with Finance teams.
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