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Design, develop and maintain data pipelines connecting laboratory, IT and enterprise systems
Build and evolve data lake/lakehouse architectures for laboratory and operational data
Develop robust ETL/ELT processes using APIs, databases and other supported integration mechanisms
Transform raw laboratory data into structured, reusable and analytics-ready datasets
Develop scalable data models supporting reporting, analytics, automation and future AI/ML
Establish data-quality checks, monitoring, logging and error-handling mechanisms

Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering
5–10 years of experience in data engineering, analytics engineering, integration engineering or a
Strong SQL skills and practical experience working with relational databases
Strong Python skills for data processing, automation and integration
Experience designing and maintaining ETL/ELT pipelines
Experience with cloud data platforms and/or data lake/lakehouse architectures

Data Platform Engineer

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