Data governance at TDIndustries today is focused primarily on data quality within CRM and ERP, with heavy emphasis on Power BI reporting. As TDIndustries builds toward a mature, lakehouse-driven data capability, the Data Governance Lead is the role that changes that trajectory.

This is a practitioner role, not a policy writer. The right candidate starts by working directly alongside the business on active data quality challenges - particularly customer data standardization in Dynamics 365 - while concurrently building the foundational governance practice. Over time, this role matures governance across four core functions: metadata management, master data management, data quality engineering, and data contracts. This is a Senior Individual Contributor role requiring up to 15% travel, reporting directly to the VP, Data, Analytics & AI, and working in close partnership with the Sr. Solution Architect and Data Product Managers.

Business Partnership & Data Quality

• Partner with business stakeholders across Construction, Facilities, and Building Services on active data quality issues - particularly in Dynamics 365 CRM/F&O - and drive structured, sustained remediation.
• Take ownership of ongoing customer data standardization efforts currently led by the business, bringing engineering rigor and tooling to accelerate progress.
• Define field-level business rules, valid value sets, and data standards for priority domains (customer 360, asset 360, Operations 360) and implement automated quality monitoring on the Snowflake platform.
• Build and maintain stewardship relationships with upstream data owners across Dynamics 365, Procore, Workday, and other operational systems.

Governance Framework & Practice Development

• Design and own the TDIndustries Data Governance Framework - data policy, data standards, quality monitoring standards, stewardship models, and supporting SOPs - built iteratively as the platform scales.
• Establish and maintain the enterprise business glossary and data dictionary as the single source of truth for entity definitions, system of record designations, and ownership boundaries.
• Stand up the Data Governance Council, define domain Data Owner and Data Steward roles, and operate governance cadences, reporting quality scorecards and adoption metrics to leadership.

Metadata Management

• Implement and operate the enterprise data catalog (Microsoft Purview preferred), enabling data discovery, lineage, and business-to-technical mapping across TD's data estate.
• • Enforce metadata standards ensuring every data asset carries documented ownership, classification, lineage, and business context; build lineage tracing from source systems through to analytics consumption.Master Data Management
• Establish MDM strategy and governance for critical domains - customer, site, project, asset, vendor, and workforce - defining system of record designations, golden record standards, and cross-system reconciliation rules.
• Serve as the decision authority for cross-system data conflicts; drive conformed dimension and reference data development to support consistent analytics across business units.Data Contracts
• Champion data contracts across the data platform - defining standards for schema, quality SLAs, and semantic commitments between data producers and consumers.
• Embed contract enforcement into data pipelines in partnership with Data Product Managers and engineering, preventing undeclared schema changes and quality degradation from reaching analytics and AI consumers.Collaboration & Team Development
• Collaborate with the Sr. Solution Architect on technical implementation of governance capabilities - ensuring governance is embedded in the platform, not layered on top of it.
• Partner with Data Product Managers to translate domain priorities into governed data product requirements and resolve cross-domain data conflicts.
• As the governance function matures, define team structure, mentor data quality engineers and stewards, and build playbooks that reduce key-person dependency.
• Continuously benchmark TD's governance maturity against DAMA-DMBOK, identifying gaps and sequencing a pragmatic roadmap that creates value at each stage.
• Perform other duties as required.

• Bachelor's degree in information management, computer science, business, or related field preferred
• 8+ years of progressive experience in data governance, master data management, data quality, or data management. 
• Demonstrated experience building a governance program from an early stage - not inheriting an established framework, but designing and standing one up. 
• Proven ability to work directly with business stakeholders on data quality remediation, translating between business language and technical implementation. 
• Hands-on experience implementing metadata management, data lineage, or data catalog solutions in a cloud data platform environment. 
• Working knowledge of MDM patterns across enterprise multi-source-system environments. 
• Familiarity with DAMA-DMBOK; formal CDMP certification a plus. 
• Experience in construction, building services, or facilities management is a significant advantage - project-based business models, work order operations, and asset-centric data are directly relevant. 

Governance & Quality Tooling 

• Data catalog and metadata management - Microsoft Purview strongly preferred; Collibra, Alation, or equivalent considered. 
• Data quality automation - Great Expectations, Monte Carlo, Soda, dbt tests, or equivalent; experience building quality monitoring into cloud data pipelines. 
• MDM platforms or pattern-based MDM implementation on cloud data platforms. 
• Data contract frameworks - Data Contract Specification, Atlan, or custom enforcement via dbt/Snowflake. 

Data Platform (Working Proficiency) 

• Snowflake - access policies, data sharing, quality monitoring, and governance implementation; sufficient depth to partner credibly with data engineers. 
• Microsoft Fabric and Power BI - semantic model governance, sensitivity labels, information protection, and RBAC. 
• dbt - data quality tests, documentation, and lineage as a governance surface. 
• Azure Entra ID and RBAC - working knowledge of identity and access management as it applies to data platform governance.