DevOps Engineer

We are looking for DevOps Engineers with strong experience in data architecture, containerization, and cloud-native deployments. The ideal candidates will have hands-on expertise in Kafka-based data pipelines, Kubernetes orchestration, CI/CD automation, and data integration within regulated environments (preferably banking/financial services). This role involves building scalable, secure, and high-performance data platforms across multiple environments.

Key Responsibilities:

• Implement and configure Helm packages across multiple environments.
• Design and manage data ingestion pipelines using Apache Kafka, ensuring high availability and low-latency data delivery.
• Translate functional and technical requirements into scalable technical solutions and workflows.
• Manage data modelling, schema registry configurations, and serialization strategies.
• Monitor, troubleshoot, and resolve issues in data pipelines, schema alignment, and data transformation processes.
• Ensure data integrity, compliance, and adherence to regulatory standards.
• Provide technical training, documentation, and ongoing support to business users and developers.
• Deploy and orchestrate containerized components using Docker and Kubernetes (including AKS and OpenShift).
• Support CI/CD pipelines, automated deployments, and infrastructure-as-code practices.
• Integrate data sources, analytics, and reporting modules to deliver actionable insights.

Requirements:

• Strong understanding of data architecture, data flows, and distributed systems.
• Proficiency in Apache Kafka (Schema Registry, topic management, event filtering).
• Extensive experience with SQL Server or similar relational databases.
• Hands-on expertise in data modelling, schema versioning, and data integration.
• Strong command of Docker for building and managing containerized applications.
• Experience deploying and managing applications on Kubernetes platforms, including AKS or OpenShift.
• Experience troubleshooting serialization issues, ingestion failures, and performing log analysis.
• Proficiency in Python, Bash, or similar scripting languages for automation.
• Comfortable working in Linux-based environments with CLI log and file management.
• Strong analytical and problem-solving skills, preferably with exposure to financial data contexts.
• Experience with DevOps tools such as Jenkins, Helm, and Git for CI/CD automation.
• Knowledge of cloud-native architecture and microservices within the banking ecosystem.
• Familiarity with data security practices, encryption standards, and GDPR compliance.
• Understanding of real-time analytics, fraud detection, or regulatory reporting use cases.