PETER PUGH-JONES
THE FINTECH INTERVIEW
PETER PUGH-JONES
TITLE: EMEA FIELD CDO, DATA STREAMING PLATFORM
COMPANY: CONFLUENT INDUSTRY: TECHNOLOGY
Peter Pugh-Jones has more than 30 years’ experience in technology strategy, transformation and infrastructure development across global sectors, specialising in governance frameworks and largescale project delivery.
for cloud and data streaming increase, banks are left in a bind.”
The industry finds itself in an unusual position. While banking moves toward modern technology stacks, maintaining existing legacy systems becomes increasingly difficult.
This creates operational risk alongside transformation challenges.
Specialised support becomes essential in this environment. Banks require expertise that bridges legacy systems and modern cloud architectures.
Simply understanding cloud technology proves insufficient without practical experience integrating it with existing infrastructure.“ That might mean working with tools that simplify complex technologies like Kafka or bringing in engineers with hands-on experience in cloud migrations,” Peter says.“ It’ s really about people who’ ve seen what works, what doesn’ t, and how to avoid common missteps.”
The demand for data engineers capable of building robust, real-time systems has increased sharply. Internal teams often possess significant expertise but face competing priorities between maintaining legacy systems and designing next-generation architecture.
This responsibility creates burnout risk and can stall transformation initiatives. Asking existing teams to simultaneously maintain critical legacy infrastructure while developing modern replacements often proves counterproductive.
“ Internal teams may be brilliant, but the additional responsibility of keeping mission-critical legacy infrastructure afloat can stretch them thin,” Peter continues.“ Asking them to simultaneously design next-gen architecture is a fast track to burnout and stalled transformation.
Building cloud cores for AI The relationship between cloud migration and AI adoption presents a complex chicken-and-egg scenario. Clean, integrated, real-time data streams prove essential for effective
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