Director, Data Governance

About the role

The Director, Data Governance, in the Global Analytics & Insights (GAI) organization, owns the governance function for Avalara’s enterprise data, metrics, and platforms - establishing the policies, controls, and practices that make GAI’s data trusted, secure, and fully compliant.

This is a founding role for this function: you’ll take over the current processes, identify areas for improvement, gaps, and other opportunities, define a roadmap and scale into a full practice as the function matures.

Responsibilities

• Function Leadership
• Assess the current state of data governance processes, tooling, and practices within GAI — identify gaps, risks, and opportunities, and develop a prioritized roadmap to address them
• Own and evolve the Data Governance function within GAI — setting the operating model, quality bar, and strategic direction for how GAI's data assets are classified, accessed, and stewarded
• Review all processes, systems, and protocol for work related to critical data, partnering with engineering to ensure processes evolve to meet the highest standards
• Maintain and mature the existing role-based access governance model for GAI — including access controls, request/review processes, periodic access reviews, and data sensitivity audits across Snowflake and GAI's data platforms
• Lead the classification of GAI's data assets against Avalara's enterprise taxonomy (Public, Internal Use, Sensitive, Restricted); drive remediation of unclassified or misclassified data
• Partner with Legal, IT, and Privacy to ensure GAI's data handling practices comply with applicable regulatory and contractual requirements, including SOC 2
• Champion development of a data catalog and metadata management capability within GAI; ensure pipelines, models, and data products are discoverable, documented, and trusted
• Establish data lineage practices that provide visibility into how data flows through GAI systems and where it is consumed downstream
• Data Access Governance & Classification
• Maintain and mature the existing role-based access governance model for GAI — including access controls, request/review processes, periodic access reviews, and data sensitivity audits across Snowflake and GAI's data platforms
• Lead the classification of GAI's data assets against Avalara's enterprise taxonomy (Public, Internal Use, Sensitive, Restricted); drive remediation of unclassified or misclassified data
• Partner with Legal, IT, and Privacy to ensure GAI's data handling practices comply with applicable regulatory and contractual requirements, including SOC 2
• Data Quality & Metadata Management
• Build and maintain a data quality framework for GAI — quality dimensions, monitoring, alerting, and remediation processes; apply particular rigor to financial metrics and reporting data given their sensitivity and downstream impact
• Review SQL models and pipeline logic to verify that implementation aligns with documented business purpose — identifying definitional drift, undocumented transformations, or logic that has diverged from stated intent
• Champion development of a data catalog and metadata management capability within GAI; ensure pipelines, models, and data products are discoverable, documented, and trusted
• Establish data lineage practices that provide visibility into how data flows through GAI systems and where it is consumed downstream
• Cross-Functional Partnership
• Serve as GAI's primary liaison to Avalara's enterprise governance, security, privacy, and AI CoE teams — ensuring GAI practices align with company-wide frameworks
• Partner with Internal Audit and Information Technology on compliance reviews, control assessments, and system-level accuracy — ensuring GAI's data systems meet enterprise audit standards
• Engage executives and cross-functional leaders on data risk, compliance posture, and governance maturity; influence adoption without formal authority over partner functions
• Partner with Data Engineering and Analytics Engineering to ensure governance requirements are built into pipelines and semantic models, not bolted on afterward

Qualifications

• 8+ years of experience in data management, data engineering, analytics, or a closely related field; ideally in a SaaS or technology business at scale
• Deep expertise in data governance fundamentals — data access controls, classification, data quality management, lineage, and metadata management
• Experience working in or alongside finance organizations — financial reporting, analytics, or financial data processes — with a strong understanding of how financial data is produced, consumed, and governed
• Strong understanding of data security and privacy compliance requirements and how they translate to technical and operational controls
• Proven ability to drive adoption without formal authority — able to influence engineering teams, business stakeholders, and executive audiences simultaneously
• Experience building governance policies, data stewardship models, and process frameworks, not just inheriting them
• Hands-on experience with Snowflake or an equivalent cloud data warehouse
• Familiarity with dbt or similar pipeline/transformation tooling — enough to partner effectively with Data Engineering, not to build pipelines directly
• Experience with data catalog or metadata management platforms (e.g., Alation, Collibra, DataHub, or similar)
• Experience with role-based access controls in cloud data environments, including conducting periodic access reviews, data sensitivity assessments, and compliance audits

Skills

• Strong understanding of data security and privacy compliance requirements and how they translate to technical and operational controls
• Proven ability to drive adoption without formal authority — able to influence engineering teams, business stakeholders, and executive audiences simultaneously
• Experience building governance policies, data stewardship models, and process frameworks, not just inheriting them
• Hands-on experience with Snowflake or an equivalent cloud data warehouse
• Familiarity with dbt or similar pipeline/transformation tooling — enough to partner effectively with Data Engineering, not to build pipelines directly
• Experience with data catalog or metadata management platforms (e.g., Alation, Collibra, DataHub, or similar)
• Experience with role-based access controls in cloud data environments, including conducting periodic access reviews, data sensitivity assessments, and compliance audits

Benefits

Total Rewards In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses. Health & Wellness Benefits vary by location but generally include private medical, life, and disability insurance. Inclusive culture and diversity Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. We also have a total of 8 employee-run resource groups, each with senior leadership and exec sponsorship.