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Oracle Data Migration Developer
2 months ago
Must-haves :
- Bachelor's degree in Computer Science, Information Systems, or a related field.
- 2+ years in Oracle Cloud Fusion projects.
- 3+ years of experience as a Data Conversion Developer with a focus on Oracle fusion data migration.
- Strong T-SQL skills for data querying and manipulation.
- SSIS experience.
- Experience with Oracle Fusion Projects Module.
- Effective communication skills for collaboration with cross-functional teams, business analysts, and stakeholders.
- Strong problem-solving skills and attention to detail.
- Plusses.
Day-to-Day :
- Insight Global is looking for an Oracle Integration Cloud Consultant to join one of our largest non-profit clients.
- This individual will be joining a large initiative to migrate their Financial System from JD Edwards to Oracle Fusion Finance.
- This position will sit fully remote in India and will need to work UK hours (part-time CST hours).
Data Extraction :
- Extract data from various source systems, including flat files, spreadsheets, legacy databases, and external APIs.
- Develop and optimize SQL queries and scripts for efficient data retrieval.
Data Transformation :
- Perform data cleansing, validation, and transformation to ensure data quality.
- Convert data from source formats to Oracle-compatible formats.
- Apply business rules and data mapping for aligning source data with target data structures.
ETL Development :
- Develop and maintain ETL (Extract, Transform, Load) processes using standard tools.
- Handle data integration tasks, including aggregation, enrichment, and consolidation.
Error Handling :
- Implement error-handling mechanisms to identify and address data conversion issues.
- Monitor and log data conversion errors, creating processes for error resolution.
Performance Tuning :
- Optimize data conversion and ETL processes for performance and scalability.
- Identify and address bottlenecks in data conversion workflows.
Data Quality Assurance :
- Conduct data quality assessments to ensure accuracy and completeness.
- Implement data validation and quality checks to identify and rectify anomalies.
Documentation :
- Create documentation for data conversion processes, including data dictionaries, flowcharts, and technical specifications.
- Testing and Validation : Plan and execute data conversion testing, including unit testing, integration testing, and user acceptance testing.
- Data Security : Implement data security measures to protect sensitive and confidential information.
- Ensure compliance with data privacy regulations and company policies.
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