Backend Developer

Backend Developer  

Calgary, canada – Onsite

Requirement:

Responsibilities include:

·       Design, develop, and maintain backend code using Java, Python programming languages.

·       Develop and manage RESTful APIs and microservices.

·       Containerize applications using Docker and create/manage Kubernetes manifests and Helm charts for deployment.

·       Deploy, manage, and scale applications within Kubernetes clusters on cloud platforms AWS, Azure, and customer’s on-prem environments.

·       Implement and manage CI/CD pipelines for automated builds, testing, and deployments.

·       Design and interact with databases (SQL and NoSQL) ensuring optimal performance and data integrity.

·       Monitor application and cluster health using tools like Prometheus, Grafana, and ELK stack; troubleshoot and resolve issues promptly.

·       Implement and enforce security best practices for applications and infrastructure within the Kubernetes environment.

·       Optimize applications for maximum speed, scalability, and resilience.

·       Stay current with emerging cloud-native technologies and Kubernetes best practices.

·       Contribute to infrastructure-as-code initiatives using tools like Terraform or Ansible.

·       Participate in code reviews and advocate for high-quality coding standards.

Required Education and Skills

·       BS or MS in Computer Science or related Engineering discipline

·       Proven experience delivering software applications

·       Solid understanding of how to build publicly exposed APIs

·       Familiarity with CI/CD principles and tools technologies: Jenkins and GitLab Runner

·       Must be self-motivated but be able to work well in a team environment

·       Team player; willing to coach junior team members and cooperate on cross-functional problem solving

·       Experience with Cloud and SaaS Development: Azure, AWS, Docker, Kubernetes.

·       Working in an Agile development environment

Desired Experience

·       Knowledge of infrastructure-as-code tools (e.g., Terraform, Ansible).

·       Understanding of networking concepts in Kubernetes.

·       Experience with serverless computing.

·       Distributed Computing: distributed job orchestration on Kubernetes, parallel execution patterns, backpressure, sharding/partitioning, fault tolerance, checkpointing; frameworks (Ray/Spark/Dask) if applicable. We are mostly interested in Ray

·       Implemented Kafka-based message-driven services and event-driven autoscaling on Kubernetes using KEDA (consumer-group scaling, DLQ/error handling, and scaling policies with performance/cost guardrails).