People Data Engineer

About the role

Build reliable, secure and scalable data products and data‑lake capabilities that power AI‑enabled applications, automations and analytics experiences across Philips. Use modern data‑engineering practices, Python, SQL and Databricks to make trusted data accessible to the People Analytics Development Pod and its business stakeholders.

Key responsibilities

• Design, set up and operate a secure, governed data lake for People Analytics and approved business use cases.
• Build, test and maintain robust data pipelines using Python, SQL, Databricks and enterprise tooling.
• Ingest, transform and prepare data from enterprise systems for analytics, AI and application use.
• Develop curated, reusable datasets and data products for the People Analytics Development Pod.
• Implement data‑quality checks, monitoring and alerting to ensure reliable data delivery.
• Collaborate with Data Scientists and Full‑Stack AI Application Engineers to provide performant, governed data access.

Required profile

• Bachelor's degree in Computer Science, Data Engineering, IT or related field, or equivalent practical experience.
• At least 2 years of professional experience in data engineering, analytics engineering or software engineering.
• Strong hands‑on SQL skills and practical Python experience for data processing and pipeline development.
• Familiarity with data‑lake concepts, governance, and modern cloud‑data platforms such as Databricks.

Required skills

• Python
• SQL
• Databricks (Spark, Delta Lake, Unity Catalog)
• Data‑lake / lakehouse design
• Data pipeline orchestration
• Data modeling and data quality
• REST APIs
• Version control (Git)
• CI/CD concepts
• Azure cloud services