Data & AI Governance Specialist

• Ability to translate business, legal or privacy requirements into practical solutions with technical teams.

• 2 to 5 years of hands-on experience in any of these areas: Data Governance, Data Quality Engineering, Analytics Engineering, AI Operations or a related area.

• Experience working with data teams to implement policies, standards or governance practices in real systems.

• Experience operating modern data catalog, metadata or documentation tools.

• Strong communication skills across business stakeholders, technical data teams and legal or privacy teams.

• Strong analytical ability to trace data quality issues back through pipelines, models or workflows and support root-cause resolution.

• A self-service mindset: you prefer clear standards, automation and enablement over manual approval gates.

• Practical understanding of AI and ML lifecycles.

• Experience with Generative AI application patterns.

• Understanding of AI cataloging, model inventories or model registries.

• Familiarity with AI bias detection or mitigation practices.

• Working knowledge of foundational AI privacy and regulatory requirements, including the EU AI Act.

• Experience with OpenMetadata, Metabase, Omni, Redshift, Claude or similar tools.

• Experience supporting semantic layer, ontology graph, access marketplace or data ownership initiatives.

• Working knowledge of foundational data privacy requirements such as GDPR and SOC 2.

Data trust is becoming one of the most important challenges in the era of AI analytics.

Self-service analytics has always required strong foundations. Now, with the rise of LLMs and AI agents, the opportunity is bigger, but so is the risk. Pointing an AI assistant at a warehouse can create a false sense of precision if the underlying data model, definitions, documentation and ownership are not clear.

As a Data & AI Governance Specialist at seQura, you will help build the foundations that allow teams to find, trust, understand and apply data and AI safely, autonomously and responsibly.

You will work at the intersection of business, data, AI, legal, privacy and security teams, translating complex requirements into clear workflows, usable standards and technical solutions.

seQura provides innovative, flexible and easy-to-use payment technologies that help merchants acquire, convert and retain more customers.

We make a difference in sales performance by tailoring our solutions to different sectors, to address their unique pain points and deliver superior results in Retail, Education, Eyewear, Repairs and Travel.

We also empower smart shopping to consumers who seek more value, convenience, and flexibility in their shopping, with new payment experiences that allow them to save, access interest-free credit, or pay in small, comfortable installments of up to 24 months.

Born in Barcelona, seQura is a privately-owned fintech, currently expanding throughout southern Europe and Latin America, growing above 50% CAGR.
Over 6000 businesses, almost 3 million shoppers, and almost 400 employees continue to rate us as one of the most loved and trusted fintechs out there, with an NPS of 87%, a Trustpilot rating of 4.7/5, and a Glassdoor rating of 4.1/5.

• Collaborate with domain stewards and analysts to maintain a unified data dictionary, clear business metric definitions and AI model documentation.

• Partner with Core Data, Data Science & AI, Business and Engineering teams to implement automated data quality checks across pipelines, health and performance monitoring dashboards/alerts.

• Manage and improve the data catalog, AI model inventory and model registry so assets are organized, searchable, well documented and easy to understand.

• Help Data Champions and AI Owners succeed by giving them clear templates, training, tooling and documentation rather than relying on manual approval gates.

• Act as the operational bridge between Legal, Privacy, Security and Data & AI teams to support GDPR, SOC 2 and EU AI Act readiness.

• Champion a culture where quality and responsible AI are collective responsibilities, supported by automation, ownership and practical enablement.

You will join the Data & AI Governance vertical, working closely with the Data Governance Lead, the wider Data & AI team and business stakeholders across seQura.

This team owns the foundations that make self-service analytics and responsible AI possible: metadata, documentation, ownership, quality standards, lineage, data and model discoverability, access governance and AI risk workflows.

• Data is treated as a product, with clear ownership, quality standards, and consumers.

• Governance acts as an enablement layer, rather than a blocker.

• Self-service systems are prioritized over manual approval processes.

• Close collaboration with domain experts helps turn business knowledge into reusable, trusted data assets.

You will onboard into seQura's Data & AI organization, understand how our data model, access groups and governance practices work today, and start researching the semantic layer foundations needed to support reliable AI-assisted analytics.

Month 2

You will start working on metadata and ontology graph initiatives, helping connect business concepts to the right data entities, definitions and ownership structures.

Month 3

You will contribute to warehouse optimization and access marketplace initiatives, helping make governed data assets easier to discover, request, use and maintain across teams.

Tech stack & environment 🛠️

You will work with tools and systems that support data cataloging, metadata management, self-service analytics, data quality, access governance and documentation.