Data Governance Specialist
Description
About Zinkworks
Zinkworks partners with leading Telecommunications and Financial Services organizations to modernize legacy systems, migrate mission-critical platforms to the cloud, and engineer AI-driven automation. From OSS transformation to rApp development and network intelligence, our teams simplify complexity and turn it into competitive advantage. Based in Ireland and operating across the EU, UK, and US, Zinkworks combines deep domain expertise with delivery excellence to help clients modernize faster and operate smarter.
Role Overview
We are seeking a Data Governance Specialist to lead the definition of data requirements underpinning AI-driven use cases within large-scale enterprise transformation programmes (e.g., APEX).
This role will focus on establishing the data foundations required for AI models and workflows, ensuring that governance, quality, lineage, and compliance considerations are embedded early—prior to implementation.
Operating at the intersection of business, data, and AI engineering, you will work closely with CTO Data Governance teams, domain Data Owners, AI/ML engineering teams, and data platform teams, ensuring alignment between governance standards, business outcomes, and technical implementation. You will also partner with business stakeholders and product owners to translate AI use cases into clear, actionable data requirements.
You will play a critical role in ensuring that AI solutions are built on trusted, well-governed, and high-quality data, enabling scalable and compliant AI adoption.
Key Responsibilities
Lead data discovery and identify all data sources required to support AI use cases
Define Critical Data Elements (CDEs) and associated metadata, ensuring clear semantic meaning and relationships
Establish data quality rules and contribute AI-specific requirements into data contracts (e.g. fields, latency, refresh rates)
Define AI data requirements including accuracy, completeness, timeliness, and availability
Specify requirements for feature stores, including reusable features, transformation logic, and update frequency
Define embedding and vector store requirements to support semantic search and contextual AI use cases
Document end-to-end data lineage to ensure traceability and trust in AI outputs
Define data lifecycle and retention policies aligned to cost, performance, and compliance needs
Identify and classify sensitive data, ensuring compliance with GDPR and other regulatory obligations
Provide input into AI data readiness assessments in collaboration with Data Governance stakeholders
Required Skills & Experience
5+ years experience in data governance, data management, or data architecture
Strong understanding of data governance frameworks (e.g., DAMA-DMBOK)
Experience defining data quality rules, metadata, and lineage
Familiarity with AI/ML data requirements, including feature engineering and model inputs
Strong SQL skills with experience working on cloud-based data platforms such as BigQuery (or equivalent)
Experience with data contracts and modern data platforms
Knowledge of data privacy regulations (GDPR)
Strong stakeholder management and communication skills
Desirable Experience
Experience working on AI/ML or advanced analytics programmes
Familiarity with feature stores, vector databases, and embeddings
Experience in telecommunications or financial services domains
Exposure to data observability and data quality tooling
Inclusion & Diversity at Zinkworks
At Zinkworks, we are deeply committed to fostering a culture of diversity, inclusion, and belonging. We believe that our strength lies in the unique backgrounds, perspectives, and experiences of our team members. By embracing an inclusive environment, we empower innovation and collaboration across all levels of our organisation. Based in Ireland, we are proud to support and engage with our local communities through meaningful initiatives that promote equity and opportunity. Our commitment extends beyond the workplace, as we actively contribute to creating a more inclusive and connected society for all.