Data Catalog & Lineage Lead

Johnson Controls•Glendale, AZ

About The Position

The Data Catalog & Lineage Lead leads enterprise metadata management, data catalog, and data lineage programs. The role establishes and governs the processes, standards, technologies, and operating models needed to provide visibility into organizational data assets. Working with Data Governance, Data Quality, Data Engineering, Enterprise Architecture, Analytics, Security, and Business Data Owners, the lead delivers trusted metadata, business context, lineage, impact analysis, and data discovery capabilities. The role serves as the primary steward of enterprise metadata and lineage strategy, ensuring data assets are discoverable, understandable, governed, and traceable throughout their lifecycle. The lead develops metadata standards and governance processes, manages enterprise catalog capabilities, establishes end-to-end lineage practices, and oversees business glossary development. The role supports impact analysis and change management, regulatory and compliance needs, and cross-functional stakeholder engagement. Success is measured through improvements in data discoverability, self-service adoption, regulatory and audit readiness, metadata quality, lineage coverage, glossary maturity, data trust, change-impact visibility, and AI and analytics readiness.

Requirements

Bachelor’s degree in Information Systems, Computer Science, Engineering, Data Management, or a related field.
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.
Experience with one or more of Microsoft Purview, Apache Atlas, Horizon Catalog in Snowflake, Data Platforms, Snowflake, Azure, Microsoft Fabric, or SQL Server.
Knowledge or experience in business glossaries, data stewardship, metadata management, data classification, data lineage, data discovery, or master data management.
Skills in SQL, data modeling, ETL/ELT processes, data architecture, impact analysis, and root-cause analysis.

Nice To Haves

Master’s degree.
Big Four 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.

Responsibilities

Develop and execute the enterprise metadata management strategy, define metadata standards, establish governance processes, create a roadmap for catalog and lineage capabilities, and promote metadata-driven decision-making.
Lead implementation and enhancement of enterprise data catalog platforms; establish processes for cataloging assets across databases, warehouses, lakes, BI platforms, analytical datasets, and APIs; maintain business-friendly documentation; improve discoverability and self-service; and drive adoption.
Define enterprise lineage standards and practices; implement end-to-end lineage across source systems, ETL/ELT pipelines, warehouses, lakes, reporting platforms, and AI/ML environments; maintain business and technical lineage views; and enable impact and root-cause analysis.
Partner with Data Governance teams to define metadata stewardship responsibilities, quality standards, ownership, and accountability; monitor metadata completeness and accuracy; and align with governance, compliance, and audit requirements.
Lead development and maintenance of enterprise business glossaries; collaborate with subject matter experts to standardize terminology and authoritative definitions; resolve duplicate or conflicting terms; and promote consistent business language.
Support application, platform, and data modernization initiatives by assessing impacts of schema changes, pipeline modifications, platform migrations, and reporting updates, and enable proactive risk management through lineage analysis.
Support regulatory, privacy, and audit requirements, including data classification, sensitive data identification, retention requirements, and traceability; provide lineage evidence during audits and compliance reviews.
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, and drive enterprise adoption of metadata best practices.