Data and AI Engineer
At a glance
Mid-level AI Engineering role at Philips (Internal Job Postings List For Philips Contingent Workers). Amsterdam · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Turn unclear requests from business teams into analytical questions, then explain your findings and challenge assumptions when needed
- Pull together Salesforce, SAP, ServiceNow and other enterprise data, checking its quality, lineage, security and governance
- Build Python and SQL data products, curated datasets and metric layers on Databricks and cloud platforms
- Analyze revenue, orders, pipeline, backlog and installed-base data to explain performance and business variances
- Develop and deploy agentic AI tools, including their evaluation, testing and adoption by business users
What you bring
- A relevant bachelor's degree plus five years of experience, or a relevant master's degree plus three years
- Hands-on Python, SQL, Spark or PySpark, Delta Lake and practical Databricks experience across development and deployment
- You have taken agentic AI solutions beyond prototypes, with evaluation, testing and production readiness in scope
- You can analyze and reconcile data, including explaining why sources or metrics differ
Who this fits
This mid-level, hands-on role suits someone who can move between data engineering, analysis and agentic AI while working with business and technical stakeholders. You’ll coordinate work across teams and communicate in English with business leaders and technical colleagues. For office-based teams, Philips expects in-person work at least three days a week.
From the employer
Job Title
Data and AI EngineerJob Description
Enterprise Informatics is Philips' software business. Decisions about where to invest, which opportunities and accounts to prioritize, and how the business will perform depend on data from CRM, ERP, service, contracts and other enterprise systems. The Data and AI Engineer works at the intersection of business analysis, data analysis, data engineering and agentic AI. The role turns ambiguous business needs into well-defined analytical problems and scalable solutions, from data discovery and rapid prototyping through deployment and adoption. It is a hands-on technical role requiring direct work in Python and SQL, alongside the ability to explain methods, data quality and business implications to senior stakeholders.
Your role:
- 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.
You’re a right fit if:
- 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
Compensation & benefits
Doing meaningful work should come with fair, transparent rewards. The base salary range for this role is €78.187 –€130.312. We determine pay within the range using objective factors, like the skills the role requires, your relevant experience and the responsibility you'll have in this role, alongside internal equity and local market considerations.
We’ll share the full approach with you during the interview process, so you can make a clear, informed decision.
How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.
About Philips
Are you ready to do the work of your life to help the lives of others? Learn more about our business, discover our rich and exciting history and learn more about our purpose.
If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care.
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