About the Opportunity This is not a traditional Data Architect role focused on reporting or modelling. My client is looking for someone who enjoys designing large-scale cloud-native data platforms, defining architectural standards, and solving complex platform challenges across distributed systems.
Hybrid | Madrid or Spain
Senior / Lead level (+8 years of experience)
Up to 85k
What You'll Work On Designing and evolving enterprise-scale data platforms
Defining cloud-native architectures on AWS
Building event-driven and real-time data solutions using Kafka
Driving platform scalability, reliability, security, and cost optimisation
Defining architectural standards and governance across teams
Providing technical leadership to internal teams and external partners
Owning end-to-end platform architecture from ingestion to consumption
Improving platform usability, self-service capabilities, and developer experience
Working closely with security, compliance, and business stakeholders
Tech Stack Cloud: AWS
Streaming: Kafka, Confluent Cloud, Confluent Platform
Infrastructure as Code: Terraform
Programming: Python, SQL
AWS Services: EKS, Lambda, Fargate, DynamoDB, MemoryDB
Nice to Have: Apache Flink
What We're Looking For Strong experience designing large-scale data platforms
Deep AWS expertise
Hands-on experience with Kafka and event-driven architectures
Experience with Terraform and Infrastructure as Code
Strong understanding of distributed systems
Experience defining architecture standards and best practices
Ability to influence technical decisions across multiple teams
Strong stakeholder management and communication skills
Experience working in regulated environments is a plus
Additional Information High-impact architecture ownership role
Enterprise-scale platform challenges
Modern cloud-native environment
Strong focus on architecture, governance, and platform strategy
International and collaborative engineering culture
Open to Data Platform Architects and Principal Engineers who enjoy solving large-scale architecture challenges across AWS, Kafka, and modern cloud-native ecosystems
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