Thermo Fisher Scientific seeks a Data Engineer II to design and optimize data pipelines on the Enterprise Data Platform, supporting R&D teams across the organization. The role involves cloud-based data solutions, real-time and batch processing, and collaboration with cross-functional teams in an agile environment.
Responsibilities
Design and optimize data pipelines for batch and real-time processing across use cases
Perform source-to-target data analysis and mapping for various business requirements
Collaborate with engineers, analysts, and stakeholders to ensure data quality in DWH and AWS platforms
Participate in agile planning, backlog refinement, and risk mitigation with leadership
Support Enterprise Data Platform architecture evolution and roadmap initiatives
Requirements
4+ years overall experience with 3+ years in data solutions delivery
2+ years building cloud BI solutions on AWS or Azure
4+ years programming in SQL, PySpark, and Python
Experience with agile, DevOps, DataOps, and DevSecOps methodologies
Knowledge of GPT, Large Language Models, and Retrieval Augmented Generation
Strong analysis, documentation, and cross-functional communication skills
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