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 Catalog & Lineage Lead is responsible for leading enterprise metadata management, data catalog, and data lineage programs. This role establishes and governs the processes, standards, technologies, and operating models required to provide comprehensive visibility into data assets across the organization.

You will work closely with Data Governance, Data Quality, Data Engineering, Enterprise Architecture, Analytics, Security, and Business Data Owners to deliver trusted metadata, business context, data lineage, impact analysis, and data discovery capabilities.

The role serves as the primary steward of enterprise metadata and lineage strategy, ensuring that data assets are discoverable, understandable, governed, and traceable throughout their lifecycle.

How you will do it

Metadata Strategy & Leadership

• Develop and execute the enterprise metadata management strategy.
• Define standards for business, technical, operational, and process metadata.
• Establish enterprise metadata governance processes.
• Create a roadmap for data catalog, lineage, and metadata capabilities.
• Promote metadata-driven decision-making across the organization.

Data Catalog Management

• Lead implementation and enhancement of enterprise data catalog platforms.
• Develop processes for cataloging data assets across databases, data warehouses, data lakes, BI platforms, analytical datasets, and APIs.
• Ensure business-friendly descriptions and documentation are maintained.
• Improve data discoverability and self-service capabilities.
• Drive user adoption of catalog solutions.

Data Lineage Management

• Define enterprise lineage standards and practices.
• Implement end-to-end data lineage across source systems, ETL/ELT pipelines, data warehouses, data lakes, reporting platforms, and AI/ML environments.
• Maintain business and technical lineage views.
• Enable impact analysis for change management.
• Support root cause analysis through lineage visibility.

Metadata Governance

• Partner with Data Governance teams to define metadata stewardship responsibilities.
• Establish metadata quality standards.
• Define ownership and accountability for metadata assets.
• Monitor metadata completeness and accuracy.
• Ensure alignment with governance, compliance, and audit requirements.

Business Glossary Management

• Lead the development and maintenance of enterprise business glossaries.
• Collaborate with subject matter experts to standardize terminology.
• Define authoritative business definitions.
• Resolve duplicate or conflicting business terms.
• Promote consistent business language across domains.

Impact Analysis & Change Management

• Support application, platform, and data modernization initiatives.
• Provide impact assessments for schema changes, pipeline modifications, platform migrations, and reporting updates.
• Enable proactive risk management through lineage analysis.

Regulatory & Compliance Support

• Support regulatory, privacy, and audit requirements.
• Assist with data classification, sensitive data identification, data retention requirements, and data traceability.
• Provide lineage evidence during audits and compliance reviews.

Stakeholder Engagement

• Collaborate with Data Governance Leads, Data Quality Leads, Data Architects, Data Engineers, Data Product Owners, Analytics Teams, Security Teams, and Compliance Teams.
• Facilitate metadata governance councils and stewardship forums.
• Drive enterprise adoption of metadata best practices.

What we look for

Required

Education

• Bachelor’s degree in Information Systems, Computer Science, Engineering, Data Management, or a related field.

Experience

• 8+ years of experience in data management, data governance, analytics, data architecture, or engineering.
• 3+ years of experience leading metadata, catalog, or lineage initiatives.
• Proven success implementing enterprise catalog and lineage solutions.
• Experience working with large-scale cloud data platforms.

Metadata & Catalog Platforms

Experience with one or more of the following:

• Microsoft Purview
• Apache Atlas
• Horizon Catalog in Snowflake

Data Platforms

• Snowflake
• Azure
• Microsoft Fabric
• SQL Server

Governance & Metadata

• Business Glossaries
• Data Stewardship
• Metadata Management
• Data Classification
• Data Lineage
• Data Discovery
• Master Data Management

Analytical & Technical Skills

• SQL
• Data Modeling
• ETL/ELT Processes
• Data Architecture
• Impact Analysis
• Root Cause Analysis

Preferred

• Master’s degree.
• Big 4 experience with PwC, Deloitte, EY, or KPMG.
• Certified Data Management Professional (CDMP).
• Microsoft Purview Certification.
• DAMA-DMBOK knowledge.
• TOGAF certification.
• Experience supporting AI and machine learning governance.
• Experience implementing metadata automation solutions.

Leadership Competencies

• Metadata Management Expertise
• Data Governance Leadership
• Data Architecture Knowledge
• Strategic Thinking
• Stakeholder Management
• Business Process Analysis
• Influence and Change Leadership
• Communication and Facilitation
• Continuous Improvement
• Cross-Functional Collaboration

Success Profile

A successful Data Catalog & Lineage Lead delivers measurable improvements in:

• Data discoverability
• User self-service adoption
• Regulatory and audit readiness
• Metadata completeness and quality
• End-to-end lineage coverage
• Business glossary maturity
• Data trust and transparency
• Change impact visibility
• AI and analytics readiness