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Join us as a Software Engineer–Confluent Kafka on AWS at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. The ideal candidate will have expertise in cloud-native technologies, distributed streaming platforms, Kubernetes orchestration, and multi-region architecture patterns.
Job Responsibility:
Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance
Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives
Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing
Stay informed of industry technology trends and innovations and actively contribute to the organization’s technology communities to foster a culture of technical excellence and growth
Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions
Implementation of effective unit testing practices to ensure proper code design, readability, and reliability
Requirements:
Design, deploy, and operate production‑grade Confluent Kafka platforms, including Kafka brokers, Schema Registry, Kafka Connect, ksqlDB, and REST Proxy, ensuring high availability, scalability, and secure data streaming across domains
Engineer and manage cloud‑native workloads on Amazon EKS, including cluster configuration, workload deployment, upgrades, scaling, and operational support in line with Barclays engineering and security standards
Apply deep working knowledge of Kubernetes primitives and patterns, including StatefulSets, operators, persistent volumes, services, ingress, and Kubernetes networking, to support stateful and distributed platforms
Build and maintain Infrastructure as Code (IaC) using Terraform and AWS CloudFormation, enabling repeatable, auditable, and compliant provisioning of cloud and platform resources
Demonstrate strong understanding of AWS core services (such as EC2, VPC, IAM, S3, EKS, CloudWatch, Route53), and apply cloud‑native design principles to achieve scalability, resilience, and cost efficiency
Implement and support containerisation standards using Docker, container registries such as Amazon ECR, and container security practices aligned with enterprise and regulatory expectations
Contribute to the design and operation of multi‑region architectures, supporting active‑active or active‑passive deployment models to meet availability, resilience, and disaster recovery objectives
Develop and maintain automation and operational tooling using Python, Bash, or Go, supporting platform automation, diagnostics, CI/CD integration, and operational efficiency
Design, develop, and operate event‑driven architectures (EDA) using industry‑standard messaging and streaming platforms, ensuring high throughput, low latency, and resilience
Provide deep expertise in stream processing concepts including event ordering, partitioning, replay, schema evolution, and exactly‑once/at‑least‑once semantics
Demonstrated, hands‑on expertise with Confluent Kafka ecosystem including topics, partitions, producers/consumers, schema registry, connectors, and operational best practices
Build and maintain stream‑processing applications using Kafka Streams, applying stateful and stateless processing patterns to support real‑time business events and data enrichment use‑cases
Strong hands‑on coding capability with a consistent focus on clean code, testability, performance, and maintainability
Contribute directly to production‑grade codebases and review peer code to enforce Barclays engineering standards and quality gates
Deliver software using Agile methodologies, actively participating in sprint planning, reviews, retrospectives, and continuous improvement
Champion engineering discipline, automation, and data‑driven decision making across delivery cycles
Strong familiarity with modern developer tooling including GitLab, DevSecOps pipelines, and secure CI/CD practices
Hands‑on experience with: Docker Desktop for local containerized development, IntelliJ IDEA or equivalent enterprise IDEs and Secure source control, branching strategies, and automated quality gates
Drive a test‑first, quality‑driven engineering culture with hands‑on experience in: Contract Testing (PACT) for consumer‑provider assurance, Unit Testing (JUnit) and integration testing, Performance & load testing (JMeter), Mutation testing to validate test effectiveness
Ensure test coverage and automation are embedded into CI/CD pipelines, not treated as post‑delivery activities
Experience deploying and operating workloads on Kubernetes (K8s), including container orchestration and scaling concepts
Demonstrate strong awareness and practical adoption of AI‑assisted engineering practices with AI coding assistants (e.g., Claude Code, GitLab Duo, Copilot or equivalent) to support code generation, refactoring, documentation, and test creation, while retaining engineering judgement and accountability
Act as a individual contributor engineer (ICE), owning end‑to‑end delivery, stability, and operational resilience of platform and infrastructure components with minimal supervision and strong engineering accountability
Work effectively within Agile/Scrum delivery models, using Jira for backlog management, delivery tracking, and sprint execution
Apply strong analytical and troubleshooting skills to diagnose and resolve complex issues in distributed, event‑driven systems
Demonstrate excellent verbal and written communication, producing clear architecture designs, decision records, and technical documentation
Collaborate closely with cross‑functional teams (engineering, DevOps, security, architecture) to deliver integrated, enterprise‑ready solutions
Exhibit strong ownership, self‑drive, and innovation mindset, staying current with cloud‑native technologies and modern engineering best practices