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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data & AI Governance Specialist - **Company:** Sequra - **Location:** Barcelona, Spain (Remote available) - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Data Validation, Data Dictionary, Data Governance, Data Infrastructure, Identity and Access Management, Metadata, Meta-Data Management, SQL Databases, Technical Data Management Systems, Data Processing, Large Language Models, Generative AI, Documentation System, Core Data, Data Analytics, Machine Learning Operations, Virtual Agents, Amazon Redshift - **Published:** September 2, 2026 - **Apply:** https://www.recruit.net/job/data-ai-governance-specialist-jobs/1D863CC66E31F306 ## About the Role * 2 to 5 years of hands-on experience in 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 with automated data quality tests. * Experience operating modern data catalog, metadata or documentation tools. * Working knowledge of foundational data privacy requirements such as GDPR and SOC 2. * Ability to translate business, legal or privacy requirements into practical solutions with technical teams. * 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. * Professional working proficiency in English and Spanish. Nice to have: 1. Practical understanding of AI and ML lifecycles. 2. Experience with Generative AI application patterns. 3. Understanding of model drift, AI cataloging, model inventories or model registries. 4. Familiarity with AI bias detection or mitigation practices. 5. Working knowledge of foundational AI privacy and regulatory requirements, including the EU AI Act. 6. Experience with OpenMetadata, Metabase, Omni, Redshift, Claude or similar tools. 7. Experience supporting semantic layer, ontology graph, access marketplace or data ownership initiatives. ## Description Gain full access to exclusive job listings from leading companies worldwide. * Verified, High-Quality Jobs Only No ads, scams, or junk-just genuine opportunities. * Focus on Real Opportunities Explore thousands of open positions tailored to your lifestyle, including flexible remote jobs. * Exclusive Resume Review Receive expert feedback with personalized suggestions to enhance your resume., 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 bridge between Legal, Privacy, Security and Data & AI teams to support GDPR, SOC 2 and EU AI Act readiness. * Support AI risk assessments and classification workflows, including low-risk and high-risk AI use cases under EU AI Act criteria. * Implement and document practical guardrails for AI transparency, human oversight, technical documentation, access control, PII masking and bias detection or mitigation. * Conduct routine audits of data and AI usage, maintaining audit-ready records of data processing and model deployment activities. * Champion a culture where quality and responsible AI are collective responsibilities, supported by automation, ownership and practical enablement. About the Data team Team mission To amplify seQura's value by enabling anyone to autonomously find, trust, understand and apply data and AI to make smarter decisions. What we own The Data & AI organization is structured around three verticals: * Data Science & AI. * Data Analytics Enablement & Governance. * Data Platform. 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. Who we work with You will collaborate closely with: * Core Data. * Data Science & AI. * Data Platform. * Legal and Privacy. * Security. * Business domain teams such as Finance, Risk and Payments. * Domain Data Champions and AI Owners. How we work * We treat governance as an enablement layer, not a blocker. * We build self-service systems rather than manual approval processes. * We care about data trust, not just data availability. * We work with domain experts to turn business knowledge into reusable, governed assets. * We use automation, documentation and clear ownership to help teams move safely without slowing them down. * We think about AI governance as a practical operating model, not just a compliance exercise. What to expect in the next 90 days Month 1 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 Our current environment includes SQL, Amazon Redshift, OpenMetadata, Metabase, Omni and Claude. You will work with tools and systems that support data cataloging, metadata management, self-service analytics, AI-assisted workflows, data quality, access governance and documentation. 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