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Philips Data Engineering Expert 
India, Tamil Nadu, Chennai 
83694321

Yesterday
Data Engineering Expert


Your role:


As a Data Engineer Expert, you will be instrumental in designing, developing and maintaining robust data pipelines and systems to support patient safety and quality activities. You will work primarily with product and post market surveillance data, utilizing Azure and Databricks to ensure that we can monitor the performance of devices while meeting regulatory requirements.

Your Role
  • Design, Build, and Maintain Data Pipelines : Develop and maintain scalable, reliable, and efficient ETL (Extract, Transform, Load) pipelines using Azure tools and Databricks to handle large datasets from medical devices in the field.

  • Data Integration : Integrate data from various sources (e.g., medical devices, regulatory systems, clinical databases) into centralized data lakes or data warehouses using Azure Data Factory, Databricks, and other relevant tools.

  • Collaborate and work with Cross-Functional Teams : Work closely with clinical, regulatory, and quality assurance teams to ensure that data collected meets regulatory requirements (e.g., FDA, ISO 13485, MDR) and supports post-market surveillance activities.

  • Data Security and Compliance : Ensure all data systems comply with industry regulations and data privacy standards.

  • Continuous Improvement: Stay up-to-date with the latest advancements in data engineering, cloud technologies (specifically Azure), and medical device industry trends, and proactively suggest improvements to existing systems.

You're the Right Fit If You Have:

  • A Master’s degree in Computer Science, Data Science, or a related field.

  • A Minimum of 6-7 years of experience as a Data Engineer or in a related role, with a focus on data integration, ETL processes, and database management.

  • Strong proficiency in Python and SQL, with hands-on experience in writing complex SQL queries and Python scripts for data processing.- MANDATORY

  • Experience with Azure cloud services, including Azure Data Factory, Azure SQL Database, Azure Data lake and Databricks.

Our hybrid working model is defined in 3 ways:

We want to be at our best:
The way we work and our workspaces are designed to support our well-being, offer career advancement opportunities, and enable us to be at our best.