MDM Analyst

Role: MDM Analyst
Location: Watsonville, CA


The MDM tech lead will help in cleansing the data for Aurora mock conversion cycles. Candidate will address the organization's data quality requirements and align with its business objectives. Candidate will design and implement sustainable data cleansing processes to address data quality issues, such as duplicates, inconsistencies, and inaccuracies. Candidate will also participate in discussions with boundary applications related to master data.

Key Responsibilities:

• Designing MDM solutions that address the organization's data quality requirements and align with its business objectives. This includes defining data models and metadata structures.
• Data Quality Framework: Develop and implement data quality frameworks, standards, and best practices tailored to Driscoll's needs. Define data quality metrics and thresholds to measure and monitor data quality levels over time.
• Data Cleansing and Remediation: Design and implement sustainable data cleansing processes to address data quality issues, such as duplicates, inconsistencies, and inaccuracies.
• Establishing metadata repositories and frameworks to capture and manage metadata related to master data entities, attributes, and relationships. Ensuring metadata integrity and alignment with data quality standards.
• Lead the interface discussions pertaining to master data with different applications

Job Requirements:

• Strong understanding of Oracle MDM concepts, principles, and best practices in customer and supplier module.
• Have extensive expertise on TCA architecture.
• Proven experience as an Oracle MDM technical lead or similar role, with a focus on data quality management
• Strong knowledge of data quality frameworks, best practices, tools and techniques
• Participate in SIT, UAT and Go-Live to represent MDM
• Experience with the Fusion Oracle cloud platform is must
• Excellent analytical, problem-solving, and communication skills.
• Ability to work effectively in cross-functional teams and manage multiple priorities in a dynamic environment

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