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Data Quality Lead

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Onsite

Data Quality Lead

Johnson Controls

Data Quality Lead

Skills

SQL QueriesData EngineeringSnowflakeDatabricksData AnalysisMachine LearningAIAWSChange ManagementComplianceRegulatory ComplianceDigital TransformationAzure

3 days ago

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Important information


Contract type:

Permanent

Location:

Milwaukee, WI, USA

Work mode:

Onsite

Published on:

17 October 2026

What they need


About Us

Johnson Controls, a global leader in thermal management, mission-critical building systems, energy efficiency, and decarbonization, helps customers use energy more productively, reduce carbon emissions, and operate with the precision and resilience required in rapidly expanding industries such as data centers, healthcare, pharmaceuticals, advanced manufacturing, and higher education.

For more than 140 years, Johnson Controls has delivered performance where it really matters. Backed by advanced technology, lifecycle services and an industry-leading field organization, we elevate customer performance, turn goals into real-world results and help move society forward.

What you will do

The Data Quality Lead is responsible for defining, implementing, and governing enterprise data quality practices to ensure trusted, accurate, complete, timely, and consistent data across the organization.

You will partner with business stakeholders, Data Governance teams, data engineers, architects, analysts, and application owners to establish data quality standards, monitor data health, drive issue resolution, and improve overall data reliability.

As the primary authority for enterprise data quality strategy, metrics, controls, and continuous improvement initiatives, you will help strengthen the data foundations supporting business operations, reporting, analytics, AI/ML, regulatory compliance, and digital transformation programs.

How you will do it

  • Develop and execute an enterprise data quality strategy aligned with business objectives.
  • Establish data quality frameworks, policies, standards, principles, operating models, and best practices.
  • Promote a strong data quality culture across business and technology organizations.
  • Lead cross-functional initiatives designed to improve data trust and usability.
  • Partner with Data Governance teams and business data stewards to identify and define critical data elements (CDEs).
  • Establish clear data quality ownership and accountability models.
  • Define data quality rules, thresholds, service-level objectives (SLOs), service-level agreements (SLAs), and operational support procedures.
  • Facilitate governance forums and data quality review boards.
  • Support compliance with applicable regulatory and audit requirements.
  • Design and implement proactive data quality monitoring frameworks and controls addressing completeness, accuracy, consistency, timeliness, validity, uniqueness, and integrity.
  • Oversee implementation of automated data quality checks within data pipelines.
  • Monitor data quality dashboards and scorecards to identify trends, risks, and improvement opportunities.
  • Drive incident management and root cause analysis for data quality issues.
  • Lead enterprise data quality assessments and remediation activities.
  • Prioritize data quality defects based on business impact and coordinate with engineering teams on corrective actions.
  • Develop enterprise data quality KPIs, scorecards, and executive reporting.
  • Communicate data quality health, risks, and opportunities to leadership and key stakeholders.
  • Partner with Business Data Owners, Data Stewards, Data Governance teams, Enterprise Architects, Data Engineers, Application Owners, Analytics teams, and Compliance and Audit teams.
  • Serve as a trusted advisor on data quality matters and influence organizational adoption of quality standards.
  • Evaluate and support implementation of enterprise data quality solutions.
  • Define data quality monitoring across Snowflake, Azure, and data integration platforms.
  • Support metadata management, data lineage, and observability initiatives.
  • Leverage automation and AI-driven capabilities to strengthen data quality monitoring and continuous improvement.

What we look for

Required

  • Bachelor's degree in Information Systems, Computer Science, Data Management, Engineering, or a related field.
  • 8+ years of experience in data management, data governance, analytics, or data engineering.
  • 3+ years of experience leading enterprise data quality programs.
  • Experience leading cross-functional initiatives within complex organizations.
  • Demonstrated experience establishing enterprise data quality frameworks and controls.
  • Experience with cloud platforms and technologies including Snowflake, Databricks, Azure, and AWS.
  • Experience with data governance capabilities, including data catalogs, metadata management, business glossaries, and data lineage.
  • Experience with SQL and data analysis tools.
  • Experience with data integration and ETL platforms.

Leadership Competencies

  • Strategic Thinking
  • Influencing Without Authority
  • Stakeholder Management
  • Data Governance Expertise
  • Root Cause Analysis
  • Continuous Improvement
  • Process Optimization
  • Change Management
  • Executive Communication
  • Team Development

Preferred

  • Master's degree.
  • Experience with KPMG, Deloitte, PwC, or E&Y.
  • Certified Data Management Professional (CDMP) certification.
  • Collibra Certification.
  • Informatica Certification.
  • Microsoft Purview Certification.
  • Knowledge of DAMA-DMBOK best practices.
  • Experience supporting AI/ML and advanced analytics initiatives.
  • Experience with data observability and DataOps practices.

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