Software Engineer – Confluent Kafka Management

hackajob is collaborating with Barclays to connect them with exceptional professionals for this role. Join us as a Software Engineer – Confluent Kafka Management 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 deep expertise in cloud-native technologies, distributed streaming platforms, Kubernetes orchestration, and multi-region architecture patterns.

To be a successful Software Engineer – Confluent Kafka Management, you should have experience with:

• 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.
• Act as a technical authority for streaming and EDA design decisions across delivery teams.
• Demonstrated, hands‑on expertise with Confluent Kafka ecosystem including topics, partitions, producers/consumers, schema registry, connectors, and operational best practices.
• Drive platform stability, performance tuning, capacity planning, and incident management for Kafka‑centric systems in line with BUK Service First and SRE principles.
• Lead the design, deployment, and operation of containerised applications on Amazon EKS, ensuring secure, scalable, and highly available Kubernetes clusters.
• Drive Ansible‑led automation strategies across cloud and streaming platforms, enabling repeatable, policy‑driven configuration, operational resilience, and DevOps efficiency while aligning with BUK security, risk, and compliance standards.
• Demonstrate advanced Kubernetes expertise, including operators, StatefulSets, persistent volumes, services, ingress controllers, and cluster networking, supporting stateful and stateless workloads.
• Establish best practices for cluster lifecycle management, upgrades, observability, and cost optimization across environments.
• Architect and operate cloud‑native solutions with deep hands‑on expertise across AWS core services
• Ensure all solutions comply with Barclays security, risk, and regulatory standards, embedding security‑by‑design and least‑privilege access models.
• Own and evolve Infrastructure as Code (IaC) practices using Terraform and CloudFormation, enabling repeatable, auditable, and scalable cloud provisioning.
• Drive automation of environment builds, platform configuration, and operational runbooks to reduce manual intervention and improve reliability.
• Design and implement multi‑region AWS architectures, including active‑active and active‑passive deployments, with clear failover, disaster recovery, and data consistency strategies.
• Apply DORA metrics (deployment frequency, lead time for change, change failure rate, MTTR) to drive delivery predictability and engineering health.
• 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.
• Working knowledge of AWS services relevant to event‑driven and streaming workloads.
• 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.

Some Other Highly Valued Skills May Include

• Operate as a senior I…