Data Architect
Job Description
Role –Platform Architect
\nTechnology – Snowflake, Confluent Cloud, CICD, Fivetran, AKS, K8
\nLocation – London, UK
\nJob Description
\nWe are seeking a highly experienced Platform Architect to lead the architecture, governance, modernization, and operational excellence of enterprise-scale Data and Integration Platforms across Snowflake, Confluent Cloud Kafka, Azure Cloud, GitHub Actions CI/CD, Kubernetes, Data Mesh, and broader integration ecosystems. The ideal candidate will combine deep technical expertise with strategic architecture leadership, strong customer engagement skills, and the ability to provide hands-on guidance across multiple platform domains. This role will be responsible for shaping the platform strategy, defining architectural standards and best practices, and driving technology transformation initiatives that deliver scalable, secure, resilient, and business-aligned solutions.
\nYour role & Responsibilities
\nDefine enterprise platform architecture, reference architecture, standards, and engineering guardrails.
\nBuild modernization roadmaps for Data, Streaming, Integration, and Platform Engineering ecosystems.
\nDrive architecture reviews, technology evaluations, and platform transformation initiatives.
\nEstablish governance, security, resilience, scalability, and cost-optimization frameworks.
\nLead Snowflake architecture covering security, governance, RBAC, data sharing, performance optimization, and multi-environment strategy.
\nDefine enterprise data platform standards and operational best practices.
\nGuide warehouse sizing, workload management, performance tuning, and cost optimization.
\nDesign event-driven architecture using Confluent Cloud.
\nDefine topic governance, schema management, security controls, HA/DR, and cluster strategy.
\nEstablish enterprise integration patterns using Kafka, Kafka Connect, APIs, and streaming architectures.
\nDefine and implement CI/CD standards using GitHub Actions.
\nDrive Infrastructure-as-Code, automation, release governance, and quality gates.
\nEstablish platform engineering practices supporting continuous delivery and automation.
\nDefine Data Mesh principles, domain ownership models, governance, metadata management, and interoperability standards.
\nEstablish integration architecture across Snowflake, Kafka, cloud platforms, APIs, ETL/ELT, and downstream systems.
\nCollaborate with business and engineering teams to enable scalable data products
\nRequired
\n•Multiple years in Platform Engineering, Cloud, Integration, or Data Platforms.
\n•must have 1 large program where the person has implemented a multi technology platform for data on cloud
\n•Strong expertise in Snowflake and/or Confluent Kafka.
\n•Experience with Confluent Cloud, Kafka Connect, Schema Registry, and event-driven architecture.
\n•Hands-on experience with GitHub Actions, CI/CD, DevOps automation, and Infrastructure-as-Code.
\n•Experience with Azure/AWS/GCP cloud platforms.
\n•Strong knowledge of Kubernetes, containerization, and cloud-native platforms.
\n•Deep understanding of Data Mesh, Data Governance, Security, and Compliance.
\n•Experience with observability, monitoring, and platform operations.
\n•Strong stakeholder management and customer-facing experience.
\n•Experience working in Agile delivery environments
