People Data Engineer

Design, build, and operate a secure, governed data lake and data pipelines to support People Analytics and AI-enabled applications across Philips.

Create, maintain, and deliver curated, reusable datasets and data products using Python, SQL, and Databricks for analytics, automation, and AI models.

Collaborate closely with Data Scientists, Full Stack AI Application Engineers, and business stakeholders to translate requirements into maintainable, governed data engineering solutions.

Bachelor's degree in computer science, data engineering, IT, software engineering, data science, or related field (or equivalent experience).

Minimum 2 years professional experience in data engineering, analytics engineering, software engineering, or a related technical field.

Strong proficiency in SQL (including query optimization), practical Python experience, and familiarity with Databricks or similar cloud data platforms.

Experience working with data pipelines, data-lake concepts (ingestion, transformation, governance), APIs, version control, and awareness of data privacy, security, and compliance requirements.

Experienced in building and operating governed data lakes or lakehouses with modern data engineering tools and platforms, especially Databricks.

Able to deliver AI- and analytics-ready data products by designing data models, data quality measures, and secure access patterns.

Comfortable working within global, matrixed organizations collaborating across technical and business teams, including privacy and compliance stakeholders.