Job Description
The Data Governance Specialist is responsible for leading the implementation of Data Governance across Viamericas, under the conceptual framework of DAMA-DMBOK. This role ensures that the organization’s data assets are properly managed, standardized, and trusted, supporting business decision-making and accelerating the transition toward a truly data-driven culture. The specialist will propose the policies, standards, domain structures, metadata definitions, and data quality rules required to establish a robust Data Governance Framework. These proposals will be presented to, and validated by, the Data Governance Committee, which is the body responsible for final approval and formal adoption. The role also leads the cross-functional analysis needed to inform these proposals, facilitates collaboration among business, technical, and operational teams, and aligns governance initiatives with the organization’s strategic processes and value chain.
In close partnership with business units, development teams, and architecture leaders, the specialist will guide the functional implementation of the enterprise data catalog, support the integration of governed data assets into operational processes, and promote Data Governance best practices throughout the organization. Additionally, the role will help introduce AI-enabled mechanisms for metadata discovery, quality monitoring, and automation to accelerate governance maturity and scalability across Viamericas.
Duties and responsibilities
- Governance Strategy and Framework
- Design and implement the Data Governance Framework aligned with DAMA principles, covering data ownership, quality, metadata, and lifecycle management.
- Define policies, standards, and procedures for data governance adoption across Viamericas.
- Develop the detailed adoption roadmap, prioritizing domains and milestones according to strategic processes and value chain.
- Establish a governance operating model, including the roles of Domain Leader, Data Administrator, and Data Steward.
Data Domain Definition and Management
- Lead the identification and mapping of corporate data domains, aligned with business capabilities and strategic processes.
- Facilitate cross-functional workshops to define domain boundaries, key concepts, critical data elements (CDEs), and metadata structure.
- Collaborate with business and development teams to ensure governed attributes are used as the official source within systems and applications.
- Document the rules, metrics, and methodologies for data quality measurement and ensure their consolidation into domain-level quality indicators.
Metadata and Catalog Management
- Lead the functional implementation of the enterprise data catalog, working closely with the Solutions Architect to evaluate and select tools that integrate seamlessly with the Data Lakehouse.
- Define metadata standards, lineage documentation, and AI-assisted data discovery procedures.
- Collaborate with Data Engineering to ensure technical metadata is captured and synchronized with business metadata.
AI-Enabled Governance and Quality Monitoring
- Propose and support the implementation of AI-driven mechanisms for metadata classification, anomaly detection, and automated data quality alerts.
- Partner with Data & A.I. teams to leverage analytics and machine learning for continuous data quality improvement.
Collaboration, Change Management, and Adoption
- Act as a change leader promoting a data governance culture across Viamericas.
- Conduct training and awareness sessions with business and IT stakeholders.
- Ensure alignment of governance practices with Data Architecture, Digital Analytics, and Data Visualization functions.
- Regularly report on adoption progress, quality indicators, and business impact of governance initiatives.
Requirements and Skills
- Experience & Technical Skills
- Proven experience in Data Governance implementation under DAMA-DMBOK or equivalent frameworks.
- Strong knowledge of data management disciplines (metadata, data quality, lineage, MDM, data cataloging).
- Experience designing and implementing governance policies and adoption roadmaps.
- Familiarity with AI-assisted data governance tools (e.g., Collibra, Alation, Atlan, Informatica, or similar).
- Solid understanding of data architecture concepts (Data Warehouse, Data Lake, Data Lakehouse).
- Hands-on experience with data modeling, SQL, and collaboration with engineering teams.
- Strong ability to translate technical data structures into business-relevant definitions.
- Excellent communication skills in both English and Spanish to bridge technical and business audiences.
- Experience facilitating cross-functional workshops and managing organizational change in data-driven environments.
- Certification or coursework in DAMA, Data Governance, or Data Management Professional (DGSP/CDMP) is a plus.
Soft Skills
- Strategic thinker with strong analytical and organizational abilities.
- Exceptional facilitation, negotiation, and stakeholder management skills.
- High sense of accountability, initiative, and attention to detail.
- Ability to lead change through influence, not hierarchy.
- Passion for building a data-driven culture that connects people, process, and technology.
Education
- Bachelor’s degree in Data Science, Information Systems, Engineering, or related field.
- Master’s degree or specialization in Data Governance, Data Management, or AI-enabled Business Intelligence is a plus.
Working Conditions
- Hybrid in Medellín, with on-site attendance three days per week.
- Hardware is set up for you to work from home.
- Performance Bonus
- Flexible hours - make your schedule.
- Diverse and multicultural work environment.
- An innovative environment with the structure and resources of a leading multinational.
- Here you can grow at the speed of your learning curve.
- This position may require weekend and evening work as we collaborate with our partners internationally on audits and in support of corporate initiatives.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
