Philip Murphy

Data Engineer @ Slice

About Philip Murphy

Philip Murphy is a Data Engineer with experience in software engineering and data processing. He has worked at CME Group and currently at Slice, specializing in ETL processes and stream processing technologies.

Work at Slice

Philip Murphy has been employed at Slice as a Data Engineer since 2021. In this role, he focuses on performing ETL processes on both real-time and batch datasets. He utilizes various technologies, including Scala, Spark, Kafka, Databricks, Airflow, KStreams, and RabbitMQ. His work contributes to the efficient handling and processing of data within the organization.

Previous Experience at CME Group

Before joining Slice, Philip Murphy worked at CME Group as a Software Engineer from 2017 to 2021. He spent four years in this position in Belfast, United Kingdom. His experience at CME Group provided him with a solid foundation in software engineering, which he has since applied in his current role.

Education and Expertise

Philip Murphy holds a BSc in Manufacturing Engineering from Waterford Institute of Technology, where he studied from 2008 to 2012. He also obtained a Higher Diploma in Computer Science from the Institute of Technology, Carlow, in 2017. Additionally, he completed a Post Graduate Certificate in Innovation, Entrepreneurship, and Enterprise at University College Dublin in 2015. His educational background supports his expertise in data engineering and stream processing.

Academic Background

Philip Murphy completed his secondary education at Kilkenny College, achieving his Leaving Certificate from 2003 to 2008. This foundational education preceded his further studies in engineering and computer science, shaping his technical skills and knowledge.

Technical Specializations

Philip Murphy specializes in performing ETL processes on datasets, both in real-time and batch formats. He has expertise in stream processing, particularly with technologies such as Kafka and KStreams. His technical skills are complemented by his experience with various cloud platforms and data processing tools.

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