Data Quality Manager

For this U.S. based position, the expected compensation range is $117,600 - $176,400 per year, which includes base pay and short-term incentive.

The compensation range for this full-time position applies to candidates located within the United States. Our salary ranges are determined by reviewing roles of similar responsibility and level. Within the salary range, individual pay is determined by several factors including performance, knowledge, job-related skills, experience, and relevant education or training. Schneider Electric also offers a comprehensive benefits package to support our employees, inclusive of medical (with member reward points), dental, vision, and basic life insurance, Benefit Bucks (credits to apply towards your benefits) flexible work arrangements, paid family leaves, 401(k) + match, well-being and recognition (including service anniversary) programs, 12 holidays per year, 15 days of paid time off per year (pro-rated in the first year of employment based on start date), opportunity to purchase company stock (eligibility depends on start date), and military leave benefits.

You must submit an online application to be considered for the position. The Company will accept applications on an ongoing basis until the position is filled.

If you believe this job posting is not compliant with applicable state pay transparency laws in the U.S., please notify the Company as soon as possible upon discovery by completing this form Schneider Electric Job Posting Compliance.

Schneider Electric has a hybrid (2- 3 days a week from the office) opportunity for a Data Quality Manager to be based in Nashville, TN, Boston, MA or Foxboro, MA.

Be part of the North America Data Office, where the mission is to build a robust operating and data governance model that accelerates data usage and business decision-making-ensuring data is documented, secured, high quality, Join an exciting team and help drive transformation on our digital journey.

Role Overview

As a Data Quality Manager, you will be a key leader responsible for driving, governing, and scaling the North America data quality program. You will ensure that the region's data is trusted, complete, compliant, and AI ready, enabling analytics, automation, and operational excellence. The position requires close collaboration with business, technology, and data teams across North America and globally. The successful candidate will define and enforce data quality standards, lead measurement programs, and leverage automation and AI/ML to strengthen data quality at scale.

Key Responsibilities

Data Quality Management

• Develop, implement, and evolve a scalable, automated data quality framework for North America.

• Define, monitor, and report on data quality KPIs, rules, and metrics across data domains.

• Ensure data is AI‑ready by establishing quality, completeness, timeliness, and accessibility criteria aligned to AI/ML and analytics use cases.

• Use AI/ML techniques for data profiling, pattern recognition, anomaly detection, and automated monitoring.

• Conduct root cause analysis and lead remediation efforts for data quality issues.

• Integrate data quality tools with the enterprise data catalog and governance platforms.

• Establish and maintain data quality best practices, playbooks, and training programs.

Governance & Compliance

• Ensure adherence to enterprise data governance policies, standards, and Data Golden Rules.

• Partner with business and technical stakeholders to maintain accurate data lineage, documentation, and metadata.

• Drive consistency and interoperability across North American data domains.

• Promote data stewardship, accountability, and adoption of data quality processes.

Project Leadership

• Manage projects in the initiation and incubation stages related to data architecture and quality.

• Influence senior stakeholders to adopt best practices and make data-driven decisions.

Primary Skills/Qualifications

• 7+ years of experience in data quality, data governance, data management, analytics, or related fields.

• Expertise with data quality tools (e.g., Informatica Data Quality Suite) and data catalog solutions.

• Experience with big data platforms (e.g., Redshift, Databricks) and ERP…