Data & AI Governance Specialist

About seQura

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.

About the role

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.

This is not a policy‑only role. At seQura, we treat governance as a product capability, not as a bureaucratic layer. You will partner directly with the Data Governance Lead to build practical systems, documentation, quality frameworks and self‑service tooling that make good data and AI usage easier for everyone.

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.

What challenges you’ll be solving

• Help seQura scale self‑service analytics with AI by making sure business questions can be mapped to the right, up‑to‑date entities in the data model.

• Collaborate with business domain teams to define what “production‑ready” means for key dashboards, metrics, datasets and AI assets.

• Partner with Core Data, Data Science & AI, Business and Engineering teams to implement automated data quality checks across pipelines, dashboards, ML workflows and AI use cases.

• Equip Domain Pods with self‑service tooling so they can test, certify and maintain their own data and AI assets against quality and risk standards.

• Monitor data health and model performance over time, tracking quality metrics, flagging anomalies and supporting root‑cause analysis when quality or drift incidents affect business operations.

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

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

• Map and update data and model lineage from raw source systems through transformations to downstream BI reports, ML features and LLM applications.

• Identify, flag and deprecate stale or redundant metrics, datasets and models, keeping the ecosystem lean, trusted and useful.

• Support the rollout of seQura’s data and AI ownership framework across business domain pods.

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

• Act as the operational…