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EPBCS Integration Specialist

Role overview

Qualifications

  • 5+ years of experience with Oracle EPBCS / Planning Cloud
  • 3+ years of experience in EPBCS data integration projects
  • 2+ years of experience working with Data Warehouse platforms such as Snowflake, Google BigQuery, or Azure Synapse
  • Strong SQL development skills

Responsibilities

  • Design the EPBCS extraction and Data Lake integration strategy
  • Develop dimension, actuals, and budget data pipelines
  • Implement data validation and reconciliation processes
  • Optimize integration performance and troubleshoot production issues

Key facts

Hard skills

About the company

Delan Associates Inc. logo

Delan Associates Inc.

  • IT Services & Consulting
  • 51–200
Delan is a global company that provides Engineering, Training, and Management Services and Solutions. Our mission is to be a worldwide leading-edge technology solutions and services provider.

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Job description

Job Description:

Project : EPBCS to Data Lake Integration

Role Summary: We are seeking an experienced EPBCS Integration Specialist to design, develop, and support the integration of Oracle Enterprise Planning and Budgeting Cloud Service (EPBCS) with enterprise Data Lake platforms. The ideal candidate will have strong expertise in Oracle EPM technologies, data integration, SQL, ETL development, and data quality management.

Experience Required:

5+ years of experience with Oracle EPBCS / Planning Cloud

3+ years of experience in EPBCS data integration projects

2+ years of experience working with Data Warehouse platforms such as Snowflake, Google BigQuery, or Azure Synapse

Required Skills:

Strong experience with Oracle EPBCS, including:

Metadata

Dimensions

Actuals

Budgets

APIs

Strong SQL development skills

ETL tools experience such as:

Informatica

Talend

Apache Airflow

Experience with data quality validation and data reconciliation

Key Responsibilities

Design the EPBCS extraction and Data Lake integration strategy.

Develop dimension, actuals, and budget data pipelines.

Implement data validation and reconciliation processes.

Optimize integration performance and troubleshoot production issues.

Develop technical documentation and operational runbooks.

Best Practices

Data Architecture

Versioned dimensions

Incremental actuals loads

Budget versioning

Maintain lineage and metadata

Data Quality

Pre-load and post-load validation

Reconciliation checks

Row count verification

Data consistency validation

Integration Patterns

Full dimension extracts

Incremental actuals extraction

Budget version management

Performance

Batch exports

Parallel extraction

Bulk data loading

Partitioning

Data compression

Deliverables

Integration architecture and data flow design

Data mapping specifications

Version-controlled ETL/ELT pipelines

Data quality validation framework

Reconciliation reports

Operational runbooks

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