Top Tech Jobs & Startup Jobs in London

Lead enterprise data architecture across regulatory, finance, risk, treasury, and trading domains. Define target-state architectures, modernization roadmaps, cloud migration strategies, data models, integration standards, governance, lineage, quality, and reporting platforms. Design resilient cloud-native data ecosystems using Azure, AWS, GCP, Databricks, Airflow, and modern engineering practices. Partner with engineering, DevOps, business, risk, finance, and compliance teams to modernize legacy platforms and deliver scalable, compliant self-service analytics.

Lead enterprise solution architecture for large-scale legacy modernization in banking and capital markets. Assess monolithic applications, integrations, databases, workflows, and reporting platforms; define cloud-agnostic target architectures using microservices, APIs, event-driven systems, Kubernetes, and Microsoft technologies. Establish migration roadmaps, high-availability and disaster-recovery designs, security, observability, resilience, and operational support models. Collaborate with business, engineering, security, operations, and client stakeholders to create implementable architecture blueprints and guide modernization delivery.

Own enterprise architecture assessments and target-state designs for complex legacy modernization programs. Define migration roadmaps, modernization guardrails, integration and data architecture standards, resilience requirements, and cloud-enabled platforms. Guide decomposition into microservices, APIs, and event-driven systems while supporting Kubernetes, DevSecOps, CI/CD, infrastructure-as-code, observability, governance, and hybrid deployments. Facilitate architecture reviews, manage risks, oversee implementation alignment, and maintain comprehensive architecture documentation across enterprise stakeholders.

Leads product and proposition development for banking, asset management, or private markets. Diagnoses complex client needs and designs integrated solutions combining financial services expertise, managed operations, data and technology transformation, AI, and external partners. Owns sector propositions, reusable product content and intellectual property, strategic opportunity shaping, account expansion, commercial logic, operating models, and proposal narratives while coordinating sales, delivery, strategy, technology, and partnership stakeholders.

Leads hands-on operational transformation across HR, Finance, Delivery, Commercial, Operations, and Technology. Identifies improvement opportunities, develops business cases, manages cross-functional dependencies, and drives implementation through measurable outcomes. Partners with senior leaders, facilitates decision-making, tracks benefits, and embeds sustainable operating model and process improvements. The role requires strong commercial judgment, analytical ability, stakeholder influence, and advanced PowerPoint and Excel skills.

Leads enterprise-wide transformation in financial services, translating strategy into change initiatives, operating models, business cases, and measurable value. Responsibilities include organisational change, commercial analysis, programme governance, risk management, executive engagement, stakeholder alignment, and benefits realisation. The role requires developing board-level presentations, managing complex portfolios, supporting implementation, and embedding sustainable operational and behavioural change.

Lead end-to-end development of production AI-enabled applications, from architecture and implementation through deployment, monitoring, and support. Build full-stack experiences, integrate models and enterprise data, implement retrieval, grounding, guardrails, evaluation, observability, security, and governance. Create reusable engineering foundations, optimize performance and operating costs, troubleshoot distributed systems, and provide technical leadership across cross-functional teams.

Design, build and optimise scalable cloud-native data platforms and pipelines using Microsoft Fabric, Azure Databricks, Synapse and ADF. Implement ETL/ELT with PySpark and SQL, ensure data governance, performance, reliability, and collaborate with data scientists and engineers to deliver production solutions.