Data Governance Director

Data Governance Director

Location: North America (100% Remote)
Type of contract: Full-time
Citizenship requirements: Permanent Resident/GC OR US Citizen required
Travel: 20% travel required

POSITION SUMMARY

The Data Governance Director is a senior consulting leader responsible for defining and scaling data governance services that help clients improve trust, usability, security, and business value of enterprise data assets. The role blends governance leadership with solution sales, solution engineering, and solution architecture, ensuring that advisory recommendations translate into deployable, measurable outcomes across analytics and data platforms.

Core Responsibilities

Governance Strategy & Operating Model

• Establish enterprise‑grade governance strategies, policy frameworks, decision rights, and implementation roadmaps for client organizations.
• Define target‑state operating models covering governance councils, stewardship structures, issue management, controls, and adoption metrics.
• Align governance priorities with regulatory, risk, analytics, modernization, and business transformation objectives.

Solution Sales & Advisory Support

• Partner with sales and account teams to shape client conversations, qualify opportunities, and translate pain points into governance‑led solution narratives.
• Support proposals, statements of work, and executive presentations by articulating value, scope, delivery approach, project plans and measurable outcomes.
• Act as a trusted subject matter expert during discovery, due diligence, and executive workshops.

Solution Engineering & Architecture Leadership

• Support the design of scalable data governance capabilities embedded into modern cloud data platforms and delivery pipelines.
• Ensure architectures (Medallion) support metadata capture, lineage, quality controls, observability, access governance, and consumption for reporting and analytics.
• Collaborate with engineering teams to convert strategy into deployable patterns, reference architectures, and implementation standards.

Data Quality, Observability, Lineage & Stewardship

• Define frameworks for data quality management, issue remediation, control monitoring, and service‑level expectations for critical data products.
• Establish lineage and observability requirements to improve transparency from source systems through transformation, storage, and reporting layers.
• Enable stewardship models that clarify accountability for business definitions, policies, exceptions, and remediation workflows.

Cross‑Functional Leadership

• Provide leadership across strategy, governance, engineering, analytics, and delivery teams to ensure integrated client outcomes.
• Coach consultants, architects, and analysts on governance best practices, reusable assets, and engagement quality.
• Promote collaboration between business stakeholders and technical teams to accelerate adoption and long‑term sustainability.

Technology Coverage

Platform / Tool	Primary Governance Relevance	Expected Director Oversight
Azure ADLS Gen2, ADF, Synapse	Data lake, ingestion, transformation, warehouse patterns	Governance controls, architecture standards, lineage and platform integration
Microsoft Purview	Catalog, lineage, classification, policy support	Metadata strategy, stewardship workflows, glossary alignment, scanning design
Power BI	Analytics consumption and semantic reporting	Trusted‑data enablement, certified data sets, lineage to executive reporting
Azure Databricks	Engineering, transformation, data products, governance at scale	Quality controls, observability standards, medallion governance patterns
Snowflake	Cloud data platform, secure sharing, governance controls	Role design, data‑domain alignment, governance operating model enablement
dbt	Transformation governance, documentation, testing	Model standards, test coverage expectations, lineage‑aware deployment practices
Alation / Collibra	Data catalog, glossary, stewardship, policy management	Business metadata design, stewardship adoption, enterprise governance rollout

Qualifications

• Professional Experience: 10+ years of progressive experience in data governance, data management, data architecture, analytics, or consulting, including leadership responsibility for enterprise‑scale initiatives.
• Consulting & Commercial Acumen: Demonstrated success supporting pre‑sales, solution positioning, proposal development, and executive stakeholder engagement in a consulting or professional services environment.
• Technical & Platform Expertise: Strong working knowledge of Azure data services, Databricks, Snowflake, dbt, and enterprise catalog/governance platforms such as Purview, Alation, and Collibra.
• Governance Domain Expertise: Deep knowledge of governance frameworks (DMBOK, DCAM, NIST, etc), stewardship, metadata management, lineage, observability, data quality, controls, and policy operationalization.
• Leadership & Communication: Exceptional ability to influence executives, lead cross‑functional teams, simplify complex concepts, and build trusted relationships with client and internal stakeholders.
• Education: Bachelor's degree in Information Systems, Computer Science, Data Management, Business, or a related field required; advanced degree preferred.

Measures of Success

• Growth of governance‑related consulting revenue and strategic account expansion.
• Successful delivery of governance roadmaps, platform designs, and operating models adopted by clients.
• Improved client outcomes in quality, lineage, stewardship adoption, and trusted analytics.
• Reusable solution assets, playbooks, and architecture patterns that scale across engagements.