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Industry (Information technology, software development, data, Senior-level)
Seniority (Information technology, software development, data, Non-profit, social work)
© Fuzu Ltd
Rainforest Alliance
Non-profit + 1 more
Description
Requirements
- Bachelor's degree in Data Management, Information Systems, Computer Science, Statistics, Business Administration, or a related field.
- 8+ years of experience in data management, data governance, or a related data discipline, including 2–3 years in a formal people management role.
- Demonstrated experience building or scaling a data governance program from the ground up, including policy development, standards definition, and stewardship models.
- Experience leading master data management (MDM) and metadata management projects at an enterprise level.
- Hands-on experience implementing or administering a data catalogue or data governance platform (e.g., Collibra, Alation, Informatica, Microsoft Purview, or similar).
- Experience with data governance frameworks, data quality methodologies, and metadata management principles, along with how governance integrates with analytics, BI, and reporting systems.
- Experience building, lead, and mentor a team, including hiring, performance management, and career development.
- Working knowledge of data privacy and regulatory frameworks such as GDPR, CCPA, or sector-specific regulations, and how they inform data sharing and ethics policies (preferred).
- Stakeholder management skills, with demonstrated ability to improve adoption of standards across teams without direct authority.
- Program management experience managing multiple complex, cross-functional projects simultaneously.
- Demonstrated change management experience.
- Ability to travel a maximum of 10% per year, nationally and internationally.
Responsibilities
- Strategy & Roadmap Leadership
- Implement and refine the enterprise data management strategy, aligned with our organizational and mission-level goals.
- Manage and evolve the data management roadmap, including prioritization methodology, trade-off decisions across competing our needs, and a regular review schedule (e.g., quarterly) with senior stakeholders.
- Translate high-level organisational goals into concrete, applicable data projects.
- Identify strategic risks (regulatory, technical, resourcing) related to data management and build mitigation plans.
- Lead change management efforts: run workshops and training to shift mindset and build our data literacy; develop communication plans for major policy or tooling rollouts.
- Implement and refine the enterprise data management strategy, aligned with our organizational and mission-level goals.
- Metadata & Master Data Management
- Lead metadata management projects to improve data discoverability, lineage transparency, and documentation.
- Manage master data modelling, hierarchy management, and golden record processes across important domains
- Ensure integration of metadata and master data solutions with analytics, reporting, and operational systems.
- Lead the ongoing adoption and optimization of our data cataloguing and lineage tooling.
- Lead metadata management projects to improve data discoverability, lineage transparency, and documentation.
- Governance, Ethics & Compliance
- Expand (and in some cases develop) frameworks and best practices for data governance, ethics, quality, metadata, and master data management.
- Oversee creation and adoption of enterprise data policies, standards, definitions, and controls.
- Ensure compliance with data-related regulatory and privacy requirements (e.g., GDPR, CCPA, and other applicable regulations).
- Expand (and in some cases develop) frameworks and best practices for data governance, ethics, quality, metadata, and master data management.
- Data Quality
- Define data quality standards, KPIs, and measurement methodologies across important domains at an enterprise level.
- Establish ongoing monitoring and reporting on data quality performance against defined KPIs.
- Define data quality standards, KPIs, and measurement methodologies across important domains at an enterprise level.
- Team Leadership & People Management
- Lead, and mentor (through indirect influence) a network of data owners and stewards, including onboarding and engagement through the data lifecycle.
- Mentor and lead your (direct) team of data professionals across data governance, data quality, and sharing and ethics.
- Lead, and mentor (through indirect influence) a network of data owners and stewards, including onboarding and engagement through the data lifecycle.
- Cross-Functional Influence & Stakeholder Management
- Lead cross-functional data governance forums (steering committees, councils, working groups) including business-side data owners and stewards outside the direct reporting line.
- Partner with engineering, analytics, product, and business leaders to agree on data priorities and roadmaps.
- Lead cross-functional data governance forums (steering committees, councils, working groups) including business-side data owners and stewards outside the direct reporting line.
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