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Manager – Data Quality and Automation

Job in Raritan, Somerset County, New Jersey, 08869, USA
Listing for: Jobtailor
Full Time position
Listed on 2026-07-13
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineering, Data Warehousing
Salary/Wage Range or Industry Benchmark: 150000 - 190000 USD Yearly USD 150000.00 190000.00 YEAR
Job Description & How to Apply Below

Responsibilities

  • Define and lead the data quality strategy for supply chain data domains (materials, suppliers, inventory, orders, logistics, and master data).
  • Establish data quality standards, metrics, and KPIs, and build dashboards to monitor data health across systems.
  • Implement data quality controls — profiling, validation rules, cleansing, and remediation workflows — across the data lifecycle.
  • Partner with data governance, data engineering, and business stakeholders to identify root causes of data issues and drive sustainable fixes.
  • Manage data quality issue resolution, including triage, prioritization, and tracking to closure.
  • Champion a culture of data ownership and accountability, working with data stewards and domain owners across the supply chain organization.
  • Support strategic initiatives and ensure alignment between operational systems and analytics platforms.
  • Drive continuous improvement through automation, AI implementation, and adoption of data quality best practices.
Requirements
  • Bachelor's degree in Information Systems, Computer Science, Supply Chain, Data Science, or a related field.
  • 10+ years of experience in data management, data quality, data governance, or analytics, with at least 4 years in a leadership or managerial capacity.
  • Proven experience defining and operationalizing data quality frameworks, metrics, and automated cleansing solutions.
  • Demonstrated experience applying AI/ML or advanced automation to data quality or data management challenges.
  • Strong knowledge of data quality tools (e.g., Informatica Data Quality, Collibra, Talend, SAP MDG, or similar).
  • Proficiency with SQL and experience working with large, complex datasets.
  • Track record of driving efficiency and process improvement in a data-intensive environment.
  • Excellent stakeholder management, communication, and problem-solving skills.
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