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Oracle Enterprise Data Quality Jobs (NOW HIRING)

Infojini Inc

Oracle ERP

Las Vegas, NV

Experience with Oracle ERP Cloud data conversion Experience with Oracle ERP Cloud Security Technical skills in the creation of BI Publisher Reports; FRS (financial reporting studio) Reports and OTBI ...

Deloitte

Oracle EPM (PBCS~PCMCS) Senior Consultant

Denver, CO · On-site

$65.25 - $82.25/hr

Experience with Oracle Enterprise Data Management * Experience with Oracle Groovy scripting for ... Meticulous attention to detail and quality of work product * Ability to build and sustain ...

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How much do oracle enterprise data quality jobs pay per hour?

As of Aug 13, 2026, the average hourly pay for oracle enterprise data quality in the United States is $56.63, according to ZipRecruiter salary data. Most workers in this role earn between $48.08 and $66.11 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Oracle Enterprise Data Quality specialist, and why are they important?

To thrive as an Oracle Enterprise Data Quality specialist, you need a solid understanding of data management principles, data quality frameworks, and experience with Oracle EDQ solutions, often supported by a degree in computer science or information systems. Expertise in Oracle Enterprise Data Quality (EDQ) software, SQL, data integration tools, and relevant certifications such as Oracle Certified Implementation Specialist are typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help in translating business requirements into technical solutions and collaborating with stakeholders. These capabilities ensure accurate, reliable data, driving informed decision-making and successful data governance initiatives within organizations.

What are some common challenges faced by professionals working with Oracle Enterprise Data Quality and how can they be addressed?

One common challenge in an Oracle EDQ role is managing the complexity of integrating data from multiple sources while ensuring data accuracy and consistency across the organization. Additionally, keeping up with evolving data governance standards and meeting business stakeholders' requirements can be demanding. To address these challenges, professionals often collaborate closely with data architects, business analysts, and IT teams, leveraging best practices in data profiling, cleansing, and matching. Continuous learning through Oracle documentation and active participation in user communities can also help professionals stay updated on new features and troubleshooting techniques.

What is the difference between Oracle Enterprise Data Quality vs Data Analyst?

AspectOracle Enterprise Data QualityData Analyst
Primary FocusData quality management, cleansing, and validation using Oracle toolsData interpretation, reporting, and analysis to support business decisions
Required SkillsData profiling, data cleansing, Oracle database knowledge, ETL processesData analysis, SQL, Excel, visualization tools, business acumen
CertificationsOracle certifications, data management certificationsData analysis certifications (e.g., Microsoft, Tableau)
Work EnvironmentData management teams, IT departments, enterprise environmentsBusiness units, analytics teams, consulting firms

Oracle Enterprise Data Quality specialists focus on maintaining data accuracy and integrity within Oracle systems, while Data Analysts interpret and analyze data to inform business strategies. Both roles require strong technical skills but serve different purposes in data management and analysis.

What is Oracle Enterprise Data Quality?

Oracle Enterprise Data Quality (EDQ) is a comprehensive data quality management tool that helps organizations assess, improve, and maintain the quality of their data. It provides features for profiling, cleansing, matching, and monitoring data across various sources. EDQ is commonly used to ensure that business-critical information is accurate, consistent, and reliable, supporting better decision-making and regulatory compliance. The platform integrates with other Oracle and non-Oracle systems, making it suitable for large-scale enterprise environments.
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Oracle Enterprise Data Quality jobs near you
Infographic showing various Oracle Enterprise Data Quality job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, 4% Contract, and 1% Nights. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $117,787 per year, or $56.6 per hour.

EPBCS Integration Specialist

Delan Associates, Inc

Jersey City, NJ

Contractor

Posted 16 days ago

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

Employment Type: CONTRACTOR

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