Unilabs
Healthcare
HeadofDataEngineering&DataProducts
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“Head of Data Engineering & Data Products at Unilabs. Skills: Data Engineering, Data Products, Data Strategy, Operational Reporting. Assess current maturity and define enterprise data platform. Drive platform-based approach leveraging modern technologies”
What You'll Achieve.
Establish scalable enterprise data foundations adopted across markets; Deliver trusted operational reporting across core domains; Deliver reusable data products across core domains; Increase adoption of self-service operational reporting; Reduce fragmented and duplicated reporting solutions; Improve operational transparency; Improve data-driven decision-making; Enable intelligent automation; Enable operational workflow orchestration; Contribute to operational efficiency; Contribute to value realization
Industry & Context.
Data-driven decision-making
What They're Looking For.
Must Have
15+ years of experience in enterprise data, analytics engineering, and data platform leadership, 5+ years in senior leadership roles in complex, multi-country environments, Proven track record in building and scaling enterprise data platforms, Proven track record in product-oriented data operating models, Deep expertise across Data Engineering, Deep expertise across Analytics Engineering, Deep expertise across Enterprise Data Architecture, Deep expertise across Data Products & Self-Service Enablement, Deep expertise across Enterprise Integration Patterns, Deep expertise across Workflow Automation & Operational Enablement, Experience leading federated or hybrid enterprise data operating models, Understanding of governance, interoperability, and scalable enterprise data delivery
Nice to Have
Experience in regulated healthcare environments and compliance-driven organizations preferred
What You'll Do.
Assess current maturity and define enterprise data platform
Drive platform-based approach leveraging modern technologies
Ensure scalable and secure multi-country data ingestion
Ensure scalable and secure data harmonization
Ensure scalable and secure data processing
Ensure scalable and secure data storage
Ensure scalable and secure access management
Ensure scalable and secure compliance controls
Establish reusable integration and data engineering patterns
Drive transition from fragmented reporting toward reusable data
Establish scalable data products across core domains
Productize operational and management reporting
Enable self-service access to trusted operational data
Support business functions in scaling operational transparency
Support business functions in scaling data-driven decision-making
Operate within a federated data and analytics model
Provide shared enterprise capabilities
Partner with business stakeholders to translate operational needs
Prioritize delivery based on measurable operational and business
Establish scalable data foundations supporting intelligent automation
Establish scalable data foundations supporting AI-supported operational workflows
Enable workflow orchestration
Enable embedded operational decision-support capabilities
Support integration of automation and AI-enabled operational tooling
Ensure alignment between intelligent automation capabilities and enterprise
Ensure alignment between intelligent automation capabilities and integrations
Ensure alignment between intelligent automation capabilities and operational
Define and implement scalable integration patterns across enterprise
Define and implement scalable integration patterns across operational
Ensure alignment with enterprise integration platforms
Ensure alignment with API strategies
Reduce fragmented and point-to-point data flows
Drive semantic consistency across enterprise data domains
Drive interoperability across enterprise data domains
Establish scalable and compliant enterprise data architectures
Support anonymized and cohort-based data provisioning
Ensure appropriate anonymization principles are embedded
Ensure interoperability principles are embedded
Ensure governance principles are embedded
Ensure traceability principles are embedded
Establish pragmatic and lightweight enterprise data governance principles
Define and support data ownership alignment
Define and support semantic consistency
Define and support data quality principles
Define and support data contract concepts
Ensure business accountability for data ownership
Ensure business accountability for data usage
How You'll Work.
Team & Collaboration
Cross-functional teams; Business stakeholders; Country functions; Business functions
Process & Methodology
Investment prioritization, ROI assessment, TCO assessment
Full Job Description
**Job Title:** Head of Data Engineering & Data Products **Location:** Porto, Portugal (preferred) _or_ Barcelona, Spain (optional) **Type:** Full-time – Hybrid working **Reports to:** Group CITO Unilabs is on a multi-year journey to become Europe’s leading diagnostics company. To achieve this, we are strengthening our ability to operate at scale across markets, leverage synergies across our network, and continuously evolve to meet the changing needs of patients, clinicians, and healthcare ecosystems. As part of our broader transformation journey to build a more agile, efficient, and patient-centred organisation, while strengthening our operational, medical, and commercial performance, we are looking to recruit a **Head of Data Engineering & Data Products** based in Porto, Portugal. This role is central to establishing scalable enterprise data foundations within UniTech, transforming a fragmented landscape into a trusted, product-driven data capability that enables operational reporting, self-service analytics, intelligent automation, and data-driven decision-making across Unilabs geographies. The Head of Data Engineering & Data Products will define and execute the enterprise data platform strategy, building scalable and reusable data capabilities serving country and functional needs across core operational domains including operations, finance, sales, and HR. The immediate focus over the next 12–18 months will be on: * establishing strong enterprise data engineering capabilities, * delivering trusted operational reporting, * productizing fragmented reporting and analytics into reusable enterprise data products, * enabling self-service operational insights, * and creating scalable data foundations for future intelligent automation and AI-supported operational workflows. The role requires a pragmatic, delivery-oriented leader capable of balancing speed, usability, governance, and scalability while driving measurable operational value across Unilabs. The current team c
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