Data and AI Engineer

Bouw aan de toekomst van healthcare informatics bij Philips

Enterprise Informatics is de softwaretak van Philips. Beslissingen over investeringen, te prioriteren kansen en zakelijke prestaties zijn volledig afhankelijk van data uit enterprise-systemen zoals CRM en ERP. Als Data and AI Engineer werk je op het snijvlak van businessanalyse, data-engineering en agentic AI. Je vertaalt complexe vraagstukken naar schaalbare oplossingen en werkt nauw samen met zowel zakelijke als technische teams.

Je krijgt de kans om impact te maken binnen een organisatie die zich inzet om de levens van mensen te verbeteren. Je werkt in een dynamische en innovatieve omgeving waar jouw expertise direct bijdraagt aan betrouwbare inzichten en datagestuurde besluitvorming.

Arbeidsvoorwaarden en aanbod

Bij Philips geloven we dat betekenisvol werk gepaard moet gaan met eerlijke en transparante beloning. We bieden een marktconform salaris en uitstekende secundaire arbeidsvoorwaarden, waaronder een pensioenregeling, reiskostenvergoeding en diverse extra beloningen. Daarnaast werken we hybride, waarbij we minimaal 3 dagen per week op kantoor samenwerken om de verbinding te behouden.

Ben jij klaar om de uitdaging aan te gaan en het verschil te maken? Solliciteer direct via de knop hieronder!

Belangrijkste verantwoordelijkheden

• Partner with Services, Sales Operations, Marketing, Business Operations and other stakeholders to translate ambiguous business questions into well-defined analytical problems, challenge assumptions where needed, and communicate clear conclusions.

• Find, acquire, explore, integrate and prepare data from enterprise systems such as Salesforce, SAP and ServiceNow, ensuring appropriate data quality, lineage, security and governance.

• Analyze commercial, financial and operational data to explain performance and support recurring business cycles, including revenue and order-intake bridges, pipeline, backlog, installed base and variance analysis.

• Build and maintain curated datasets, Python/SQL data solutions, and semantic and metric layers on the Databricks Lakehouse and cloud platforms, with Azure preferred and AWS experience valued.

• Rapidly prototype and productionize agentic AI solutions that put trusted insights into business users' hands. Design agent tools and skills, curate semantic metadata, create evaluation suites, and use modern AI development harnesses and coding agents while maintaining sound Git, testing and CI/CD practices.

• Coordinate cross-functional data, analytics and AI initiatives from requirements through deployment, testing, validation and adoption, working effectively across business and technical teams.

• Proactively contribute to data and AI strategy and roadmap definition, evaluate emerging technologies, and share reusable methods and best practices across the team.

Vereisten

• Bachelor's or Master's degree in Computer Science, Information Management, Data Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or an equivalent field.

• Minimum 5 years of relevant experience with a Bachelor's degree, or 3 years with a Master's degree, in data handling, analytics, data engineering, AI solution development or equivalent.

• Strong hands-on Python and SQL skills, including experience with Spark or PySpark, Delta Lake and practical software development practices.

• Practical Databricks experience spanning notebooks, Lakehouse/Delta, jobs or workflows, applications or agents, and deployment pipelines.

• Demonstrated hands-on experience building agentic AI solutions beyond a proof of concept, including evaluation, testing and production-readiness considerations.

• Strong data analysis capability, including statistical methods, data processing, reconciliation, and the ability to explain why data sources or metrics disagree.

• Experience with cloud platforms, preferably Azure; AWS experience is also relevant.

• Ability to coordinate cross-functional work, gather requirements, and communicate clearly in English with business leaders and technical stakeholders.

• Practical analytics-engineering experience with commercial and financial data, including revenue, subscription or licence models, pipeline, backlog and installed base, and related enterprise systems such as Salesforce, SAP and ServiceNow, ideally within a B2B software or technology business

• Modern agent frameworks and protocols, LLM evaluation practices, semantic modelling, dbt or Databricks metric views, and Power BI.

• Healthcare, medtech or another regulated industry is preferred

Secundaire arbeidsvoorwaarden

• Extra beloning (bijv. 13e maand, vaste eindejaarsuitkering)
• Prestatiegebonden beloning
• Pensioen
• Reiskostenvergoeding