Manager, Data Quality Operations

Johnson & Johnson Johnson & Johnson · Pharma · Titusville, NJ +9

Manager for Data Quality Operations at Johnson & Johnson, responsible for ensuring the accuracy, completeness, and consistency of data within master data management workflows. This role involves defining data standards, implementing validation rules, monitoring data health, coordinating remediation efforts, and collaborating with business and IT partners to ensure data trustworthiness for decision-making and compliance with regulatory requirements. The position focuses on process optimization, automation, and reporting on data quality KPIs within a regulated industry.

What you'd actually do

  1. Lead and oversee activities to ensure the accuracy, completeness, and consistency of data, acting as a crucial link between business operations and IT, defining data standards, implementing validation rules, monitoring data health, and overseeing remediation efforts to ensure data is trustworthy for decision-making.
  2. Contribute to the definition of data quality policies, standards, and targets.
  3. Review data for errors, inaccuracies, or missing information.
  4. Lead root-cause analysis of data quality errors and coordinating remediation plans with teams to rectify issues.
  5. Work with Data Stewards, IT, Supply Chain functions, and Operations to align data management systems, ensure data integrity, and enforce validation rules.

Skills

Required

  • Deep expertise in enterprise ERP systems (e.g. SAP/S4HANA) & familiarity with related systems.
  • Advanced proficiency in Microsoft Excel, Power BI, Tableau, and/or SQL for data validation & reporting.
  • Strong understanding of master data governance principles, data lifecycle management, and related best practices.
  • Exceptional analytical and problem-solving skills, with a focus on data quality improvement.
  • Strong organizational and prioritization skills to succeed in handling multiple priorities in a fast-paced environment.
  • Ability to build strong collaborative relationships, influence multiple partners, and establish common goals and objectives without sacrificing outcomes.

What the JD emphasized

  • regulatory requirements
  • data quality
  • master data management