
Infrastructure Engineer - Contract - Hybrid
Pelmorex
Posted about 14 hours ago
Background in meteorology is a “nice to have”, but if you don’t, don’t worry you will be working closely with our Meteorology R&D team and have the support of the current development team.Â
Design and implementation of Meteorological infrastructure core services that are currently running under Kubernetes (AWS EKS) with Istio Service mesh, EC2 instances, ECS Clusters and deployed under Jenkins CI/CD pipeline via Helm, SSM and bash deployment scripts. Core services run with AWS S3, SQS, SNS, FSx, ECS, EC2, Elasticache and ALB/NLBÂ resources. Improve monitoring system running under Prometheus, Grafana and Kibana.
Use AI-assisted development tools and workflows to improve productivity, accelerate delivery, enhance code quality, support troubleshooting, and streamline operational tasks while maintaining quality and accountability.
Provide technical advice and produce effort estimates on the various work required; execute work based on priorities.
Work with cross-functional teams to ensure all systems function as intended and without impediment to existing products or processes. This includes the development and/or integration of monitoring systems.
Work with Technology Operations team to ensure end-to-end data monitoring in software design, from data acquisition to delivery.
Use knowledge of databases and database technology to create applications which are distributed, multi-tier, and able to service large volumes of data.
Provide support to our operational teams for the relevant production systems and ensure services stay available and stable.
Maintaining operational runbooks, automation playbooks, and reliable cloud infrastructure procedures for production systems.
Roles, responsibilities and duties may evolve and change over time.
Degree or diploma in Computer Science, Engineering, Mathematics, or equivalent practical experience.
Minimum 3+ years of experience designing, implementing, and managing containerized environments using Docker and Kubernetes across platforms such as CloudStack, Proxmox, EKS & GKE.
Strong knowledge of cloud platforms and infrastructure technologies including AWS, GCP, CloudStack, and Proxmox.
Experience with core networking concepts including TCP/IP, NAT, DNS, load balancing, and firewalls.
Strong experience building and supporting production-grade distributed systems in Linux environments.
Experience developing production applications in one or more of the following languages: Go, Python, C/C++, or Rust.
Strong scripting and infrastructure automation experience using technologies such as Python, Bash, Terraform, Helm, Terragrunt, Groovy, or JavaScript.
Understanding of data structures, algorithms, and performance optimization concepts.
Experience designing and supporting highly available, scalable systems handling large volumes of data.
Experience with relational and NoSQL databases, including caching technologies such as Redis or AWS ElastiCache.
Experience with CI/CD practices and tools such as Jenkins or similar platforms.
Experience building and consuming REST-based APIs and services.
Familiarity with security best practices and secure infrastructure design principles.
Experience with monitoring and observability tools such as Prometheus, Grafana, ElasticSearch, Kibana, Jaeger and Kiali.
Understanding of cloud cost optimization, including balancing performance, reliability, scalability, and operational efficiency.
Strong problem-solving and communication skills with the ability to gather requirements, whiteboard solutions, and collaborate effectively across teams.
Experienced in maintaining operational runbooks, automation playbooks, and reliable cloud infrastructure procedures for production systems.
Experience with AI/ML infrastructure or platforms is considered an asset.
Keen interest in data and data mining, problem solving
Experience with spatiotemporal data sets and scientific data formats including netCDF, HDF, GRIB and BUFR would be a plus.
Experience in Ansible.
Education or experience in applying ML/AI to augment data analysis
Have strong analytical, problem-solving, and troubleshooting skills with the ability to diagnose issues and drive solutions.
Bring curiosity and creative thinking to solving complex technical challenges.
Thrive in fast-paced environments, effectively managing priorities and staying focused under tight deadlines.
Can work independently with minimal supervision while consistently delivering on commitments.
Are an engaged, collaborative team player who builds strong relationships and enjoys helping others succeed.
Have a natural curiosity about data: especially understanding source data such as meteorological data, what it means, and how it can create value.
Possess strong written and verbal communication skills.
Have strong organizational skills and value clear, effective documentation
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