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Tech Stack
Tools & technologiesAzureCloudERP
About the role
Key responsibilities & impact- Assess current maturity and define a scalable enterprise data platform strategy serving all markets
- Drive a platform-based approach leveraging modern technologies (e.g. Azure, Fabric, Databricks or equivalent)
- Ensure scalable and secure:
- multi-country data ingestion and harmonization
- processing and storage capabilities
- access management and compliance controls
- Establish reusable integration and data engineering patterns across enterprise and operational systems
- Drive the transition from fragmented reporting toward reusable enterprise data products
- Establish scalable data products across core domains:
- Operations
- Finance
- Sales / Commercial
- HR
- Productize operational and management reporting into trusted, scalable, near real-time self-service capabilities
- Enable self-service access to trusted operational data for business users, including operational managers and country functions
- Support business functions in scaling operational transparency and data-driven decision-making
- Operate within a federated data and analytics model where business functions continue to define priorities, KPIs, analytical requirements, and use cases
- Provide shared enterprise capabilities enabling scalable engineering, reusable products, operational enablement, and self-service reporting
- Partner with business stakeholders to translate operational needs into scalable enterprise data products
- Prioritize delivery based on measurable operational and business impact
- Establish scalable data foundations supporting intelligent automation and AI-supported operational workflows
- Enable workflow orchestration and embedded operational decision-support capabilities integrated into enterprise platforms and processes
- Support integration of automation and AI-enabled operational tooling into the enterprise ecosystem
- Ensure alignment between intelligent automation capabilities and enterprise data products, integrations, and operational workflows
- Remain clearly separated from clinical AI development, commercial AI products, and standalone AI research functions
- Define and implement scalable integration patterns across:
- enterprise systems (ERP, CRM, HR)
- operational systems (LIS, RIS, imaging, operational platforms)
- Ensure alignment with enterprise integration platforms and API strategies
- Reduce fragmented and point-to-point data flows through reusable integration and data product patterns
- Drive semantic consistency and interoperability across enterprise data domains
- Establish scalable and compliant enterprise data architectures supporting anonymized and cohort-based data provisioning capabilities for approved analytics, research, operational, approved external research and future data-sharing use cases
- Ensure appropriate anonymization, interoperability, governance, and traceability principles are embedded into enterprise data products and integration patterns
- Establish pragmatic and lightweight enterprise data governance principles focused on scalability, usability, and operational value delivery
- Define and support:
- data ownership alignment
- semantic consistency
- data quality principles
- data contract concepts between source systems and consuming products
- Ensure business accountability for data ownership and usage
- Ensure compliance with GDPR and relevant healthcare regulations
- Implement secure and auditable data access principles
- Define governance and access principles supporting compliant anonymized data usage, cohort-based analytics, and approved external data-sharing scenarios in alignment with regulatory and security requirements
- Define and manage the enterprise data technology stack with strong focus on simplicity, scalability, and cost optimization
- Evaluate and optimize modern cloud-native capabilities and tooling
- Manage relationships with data, integration, and automation vendors and partners
- Demonstrated ability to define and execute enterprise-wide data strategies aligned with measurable operational and business value
- Strong experience in enterprise data engineering, data products, and operational reporting enablement
- Proven track record in delivering scalable self-service and data democratization capabilities
- Ability to operate at executive level, influencing C-level stakeholders and business leaders
- Strong financial and portfolio management capabilities, including investment prioritization, ROI/TCO assessment, and cost optimization
- Drive data literacy and data adoption across the organization
- Experience in regulated environments (healthcare strongly preferred)
- Strong familiarity with modern enterprise data stacks including:
- Azure (Fabric), Databricks or equivalent
- enterprise integration platforms and APIs
- ERP, CRM, LIS/RIS and operational systems integration
- Experience in workflow automation, orchestration, and operational data enablement environments
- Experience working within federated or hybrid operating models and decentralized business environments
- Experience building and scaling high-performing multidisciplinary teams across:
- data engineering
- analytics engineering
- data products
- automation and orchestration capabilities
- Strong vendor and partner management capabilities
- Pragmatic and outcome-driven mindset balancing:
- standardization vs flexibility
- speed vs scalability
- innovation vs cost efficiency
- Establishment of scalable enterprise data foundations adopted across markets
- Delivery of trusted operational reporting and reusable data products across core domains
- Increased adoption of self-service operational reporting
- Reduction of fragmented and duplicated reporting solutions
- Improved operational transparency and data-driven decision-making
- Enablement of intelligent automation and operational workflow orchestration capabilities
- Contribution to operational efficiency and value realization
Requirements
What you’ll need- 15+ years of experience in enterprise data, analytics engineering, and data platform leadership, including at least 5 years in senior leadership roles in complex, multi-country environments
- Proven track record in building and scaling enterprise data platforms and product-oriented data operating models
- Deep expertise across:
- Data Engineering
- Analytics Engineering
- Enterprise Data Architecture
- Data Products & Self-Service Enablement
- Enterprise Integration Patterns
- Workflow Automation & Operational Enablement
- Experience leading federated or hybrid enterprise data operating models
- Strong understanding of governance, interoperability, and scalable enterprise data delivery
- Experience in regulated healthcare environments and compliance-driven organizations preferred (strong asset)
Benefits
Comp & perks- 🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Unilabs Website LinkedIn All Job Openings 10,000+ employees ⚕️ Healthcare Insurance 💊 Pharmaceuticals Healthcare Insurance
- Pharmaceuticals Unilabs is a leading international provider of diagnostic services, offering comprehensive laboratory, imaging, and pathology services across fifteen countries. With over 30 years of experience in the healthcare sector, Unilabs partners with pharmaceutical companies to support clinical trials and has contributed to more than 3,000 studies. The company's CARE BIG culture emphasizes quality service, customer orientation, and collaboration. Unilabs operates in multiple regions including Europe and the Middle East, making a significant impact on the health of millions every day by providing reliable and personalized diagnostic services. Head of Data Engineering, Data Products Job not on LinkedIn 🔥 1 hour ago 🏢🏡 Porto – Hybrid ⏰ Full Time 🔴 Lead 🚰 Data Engineer Azure Cloud ERP Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
- Assess current maturity and define a scalable enterprise data platform strategy serving all markets
- Drive a platform-based approach leveraging modern technologies (e.g. Azure, Fabric, Databricks or equivalent)
- Ensure scalable and secure:
- multi-country data ingestion and harmonization
- processing and storage capabilities
- access management and compliance controls
- Establish reusable integration and data engineering patterns across enterprise and operational systems
- Drive the transition from fragmented reporting toward reusable enterprise data products
- Establish scalable data products across core domains:
- Operations
- Finance
- Sales / Commercial
- HR
- Productize operational and management reporting into trusted, scalable, near real-time self-service capabilities
- Enable self-service access to trusted operational data for business users, including operational managers and country functions
- Support business functions in scaling operational transparency and data-driven decision-making
- Operate within a federated data and analytics model where business functions continue to define priorities, KPIs, analytical requirements, and use cases
- Provide shared enterprise capabilities enabling scalable engineering, reusable products, operational enablement, and self-service reporting
- Partner with business stakeholders to translate operational needs into scalable enterprise data products
- Prioritize delivery based on measurable operational and business impact
- Establish scalable data foundations supporting intelligent automation and AI-supported operational workflows
- Enable workflow orchestration and embedded operational decision-support capabilities integrated into enterprise platforms and processes
- Support integration of automation and AI-enabled operational tooling into the enterprise ecosystem
- Ensure alignment between intelligent automation capabilities and enterprise data products, integrations, and operational workflows
- Remain clearly separated from clinical AI development, commercial AI products, and standalone AI research functions
- Define and implement scalable integration patterns across:
- enterprise systems (ERP, CRM, HR)
- operational systems (LIS, RIS, imaging, operational platforms)
- Ensure alignment with enterprise integration platforms and API strategies
- Reduce fragmented and point-to-point data flows through reusable integration and data product patterns
- Drive semantic consistency and interoperability across enterprise data domains
- Establish scalable and compliant enterprise data architectures supporting anonymized and cohort-based data provisioning capabilities for approved analytics, research, operational, approved external research and future data-sharing use cases
- Ensure appropriate anonymization, interoperability, governance, and traceability principles are embedded into enterprise data products and integration patterns
- Establish pragmatic and lightweight enterprise data governance principles focused on scalability, usability, and operational value delivery
- Define and support:
- data ownership alignment
- semantic consistency
- data quality principles
- data contract concepts between source systems and consuming products
- Ensure business accountability for data ownership and usage
- Ensure compliance with GDPR and relevant healthcare regulations
- Implement secure and auditable data access principles
- Define governance and access principles supporting compliant anonymized data usage, cohort-based analytics, and approved external data-sharing scenarios in alignment with regulatory and security requirements
- Define and manage the enterprise data technology stack with strong focus on simplicity, scalability, and cost optimization
- Evaluate and optimize modern cloud-native capabilities and tooling
- Manage relationships with data, integration, and automation vendors and partners
- Demonstrated ability to define and execute enterprise-wide data strategies aligned with measurable operational and business value
- Strong experience in enterprise data engineering, data products, and operational reporting enablement
- Proven track record in delivering scalable self-service and data democratization capabilities
- Ability to operate at executive level, influencing C-level stakeholders and business leaders
- Strong financial and portfolio management capabilities, including investment prioritization, ROI/TCO assessment, and cost optimization
- Drive data literacy and data adoption across the organization
- Experience in regulated environments (healthcare strongly preferred)
- Strong familiarity with modern enterprise data stacks including:
- Azure (Fabric), Databricks or equivalent
- enterprise integration platforms and APIs
- ERP, CRM, LIS/RIS and operational systems integration
- Experience in workflow automation, orchestration, and operational data enablement environments
- Experience working within federated or hybrid operating models and decentralized business environments
- Experience building and scaling high-performing multidisciplinary teams across:
- data engineering
- analytics engineering
- data products
- automation and orchestration capabilities
- Strong vendor and partner management capabilities
- Pragmatic and outcome-driven mindset balancing:
- standardization vs flexibility
- speed vs scalability
- innovation vs cost efficiency
- Establishment of scalable enterprise data foundations adopted across markets
- Delivery of trusted operational reporting and reusable data products across core domains
- Increased adoption of self-service operational reporting
- Reduction of fragmented and duplicated reporting solutions
- Improved operational transparency and data-driven decision-making
- Enablement of intelligent automation and operational workflow orchestration capabilities
- Contribution to operational efficiency and value realization 🎯 Requirements
- 15+ years of experience in enterprise data, analytics engineering, and data platform leadership, including at least 5 years in senior leadership roles in complex, multi-country environments
- Proven track record in building and scaling enterprise data platforms and product-oriented data operating models
- Deep expertise across:
- Data Engineering
- Analytics Engineering
- Enterprise Data Architecture
- Data Products & Self-Service Enablement
- Enterprise Integration Patterns
- Workflow Automation & Operational Enablement
- Experience leading federated or hybrid enterprise data operating models
- Strong understanding of governance, interoperability, and scalable enterprise data delivery
- Experience in regulated healthcare environments and compliance-driven organizations preferred (strong asset) Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs
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Hard Skills & Tools
data engineeringanalytics engineeringenterprise data architecturedata productsself-service enablemententerprise integration patternsworkflow automationoperational enablementdata governancedata quality principles
Soft Skills
leadershipinfluencing stakeholdersfinancial managementportfolio managementdata literacyoutcome-driven mindsetcollaborationcommunicationstrategic thinkingproblem-solving