Role overview

As Data Engineer Manager, you will own the data platform that powers our AI programmes, analytics and reporting. Reporting to the Solutions & Platform Lead and based in Madrid, you will lead the Foundations build: defining the architecture, engineering standards, roadmap and delivery team that brings the platform to life.

This is a hands-on leadership role with a strong technical core. You will guide the engineering side of the data quality programme, shape the Azure-based platform architecture, and work closely with AI, business and technology stakeholders to deliver trusted data products that support guest experience, commercial performance and operational excellence.

Main responsibilities

- Lead the engineering workstream for data quality, including issue discovery, sizing, root-cause analysis, historical correction and weekly KPI monitoring.
- Own and evolve the target data architecture on Azure, covering ingestion, datalake, data warehouse and serving layers for AI use cases.
- Turn the Foundations programme into a clear roadmap and backlog, delivering in increments that unlock value early.
- Build and lead a high-performing data engineering team, including hiring, coaching and performance management.
- Manage external partners and vendors through clear scope, acceptance criteria and delivery governance.
- Define and enforce engineering standards across coding, testing, CI/CD, orchestration, naming, documentation and code review.
- Embed data quality, validation, referential integrity, matching, observability, lineage and SLA controls into the platform.
- Ensure security, access control, guest data protection and FinOps principles are applied by design.
- Partner with AI Project Managers, AI Engineers and Data Scientists to translate data needs into realistic delivery commitments.
- Prepare clear reporting on roadmap progress, data quality KPIs, incidents, risks, SLAs and cloud spend for senior stakeholders.

What success looks like in the first 12 months





- The initial catalogue of priority data issues is fully sized, assigned and dated, with unmeasured layers reconciled.
- Agreed historical corrections are implemented, monitored and sustained at target KPI levels.
- Weekly KPI reporting is established for all open issues, with clear escalation when measures do not improve.
- The Foundations roadmap is agreed and delivered within tolerance, enabling at least two AI use cases in production.
- Engineering standards are adopted by the team and partners, with monitoring and SLAs in place on critical datasets.
- The team is built to plan, and external partners are delivering against agreed acceptance criteria.
- Business and technology stakeholders view you as the person who makes data commitments and keeps them.

Required qualifications and experience

- 8+ years’ experience in Data Engineering or cloud data platforms.
- 2–3+ years’ experience leading engineers or a platform workstream.
- Proven experience designing and delivering enterprise data platforms in the cloud, preferably Azure.
- Strong hands-on skills in SQL, Python and PySpark.
- Deep understanding of ETL, batch and streaming, data modelling, lakehouse and warehouse architectures, and relational and NoSQL databases.
- Practical experience with data quality at scale, including profiling, matching, deduplication and historical correction.
- Experience with DevOps and DataOps practices, including Git, Docker, orchestration, CI/CD and infrastructure as code.
- Knowledge of data governance, security, event-driven architectures and API integrations.
- Experience managing external partners or vendors in a multi-stakeholder environment.




- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics or a related field.
- Fluent English; Spanish is an advantage.

Desired skills and competencies

- Technical credibility and sound judgement in platform design decisions.
- Strong business acumen, with the ability to prioritise by commercial value and impact.
- Clear, concise communication with both technical and non-technical audiences.
- A collaborative leadership style that develops people and raises team capability.
- Comfort operating in a fast-moving environment with multiple priorities and stakeholders.
- Familiarity with hospitality, travel or consumer data environments, including PMS, CRS, CRM or revenue management data.
- Understanding of the data foundations required for AI and GenAI workloads.

What we offer

At Sani/Ikos Group, you will join a purpose-led organisation shaped by Philoxenia, genuine hospitality and a commitment to thoughtful design and meaningful experiences. We offer:

- The opportunity to shape a strategic data platform with real business impact.
- A collaborative environment where your expertise will influence AI, analytics and operational decision-making.
- The chance to work with talented teams across technology, business and external partners.
- A culture that values development, responsibility and continuous improvement.
- The opportunity to contribute to a leading group recognised for sustainable tourism and responsible practices.

Our culture and values

Sani/Ikos Group places people at the centre of its success. We are committed to creating an inclusive, supportive environment where individuals feel valued, empowered and able to grow. Our culture is grounded in:

- Philoxenia, the Greek tradition of welcoming others with generosity and care.
- Excellence in guest experience and service.
- Collaboration, accountability and integrity.
- Sustainable growth and responsible business practices.
- Continuous learning and development.

📌 Data Engineer Manager (Madrid)
🏢 Sani/Ikos Group
📍 Madrid