Reads like an Analytics Engineer role: dbt models and clean tables.
Amsterdam
Live, first seen by us 52 days agoCompensation & 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.Read the full posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Translate ambiguous business questions into defined analytical problems
Find, integrate and prepare data from Salesforce, SAP and ServiceNow
Analyze revenue, pipeline, backlog and installed base performance
Build and maintain curated datasets and semantic layers on Databricks
Prototype and productionize agentic AI solutions for business users
translate ambiguous business questions into well-defined analytical problems
Find, acquire, explore, integrate and prepare data from enterprise systems such as Salesforce, SAP and ServiceNow
Analyze commercial, financial and operational data to explain performance
Build and maintain curated datasets, Python/SQL data solutions, and semantic and metric layers on the Databricks Lakehouse
Rapidly prototype and productionize agentic AI solutions that put trusted insights into business users' hands.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 52
Up longer than most. Similar jobs usually come down between day 6 and day 48.
Well past Philips’s usual: its jobs come down by about day 21.
From 1,469 similar postings that came down, and 54 of Philips’s. Coming down is not always a hire.
13 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Job 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:
- 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.
- 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.
- 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.
- 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.
- 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
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New Analytics Engineer postings at the employers we follow are down 9% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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:
You’re a right fit if:
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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Selected passages from the saved posting. Check the full description for conditions and exceptions.
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.
Amsterdam
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.