Oracle EPM EPBCS Data Integration- AI Agent Specialist

Oracle EPM EPBCS Data Integration- AI Agent Specialist

Duration: 12 Months + Extension

Bill Rate: $85/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 multiyear 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:

• Data Integration / Data Exchange
• Data Management (FDMEE concepts)
• EPM Automate
• 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:

• Data validation
• Variance analysis
• Intercompany reconciliation
• Narrative generation
• 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 :
• Monthly close
• Forecast cycles
• Annual planning
• 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.