Senior Platform Developer

 

Worker Sub-Type:

Regular

 

Job Description: 

About Radar BlackBerry Radar is a rapidly growing IoT platform that enables real-time tracking and analytics for thousands of trailers, containers, and high-value assets across North America. Learn more. Our platform has achieved strong market traction, with a fast-expanding device footprint and a lean, highly skilled engineering team tackling challenges in big data, cloud architecture, and performance optimization as adoption accelerates. Radar is at a critical inflection point. We’ve established product-market fit, our install base is scaling quickly, and our platform processes more data each month than ever before. We’re investing heavily in next-generation architecture to support the next five years of innovation and growth. Why This Role Matters Every new customer adds more devices, more data, and more opportunities to innovate. We’re expanding our engineering team to build the next generation of Radar’s cloud platform, focusing on:

• High-volume telemetry ingestion and big data pipelines

• Cloud re-architecture for scalability and resilience

• Advanced reporting and analytics

• API expansion and next-gen customer experiences

• Performance and reliability engineering

 • Modern DevOps tooling in a microservices environment Our Tech Stack

 • Backend: Node.js, Express, NATS

• Data: MySQL, Redis, Elasticsearch

• Analytics: Flink, Cube.js, StarRocks, Iceberg

• Cloud: AWS

• Frontend: React

• Platform: Docker, Kubernetes, ECS, Jenkins What You’ll Do

 • Design, deploy, and manage Kubernetes clusters and containerized workloads across development, staging, and production environments

• Build and maintain CI/CD pipelines using Jenkins for automated testing, building, and deployment of microservices

• Maintain and improve Jenkins infrastructure, shared libraries, and pipeline templates

 • Develop infrastructure-as-code using tools like Terraform and Helm to automate provisioning and configuration

• Create integrations between Kubernetes and internal systems (monitoring, logging, databases, etc.)

• Administer and optimize Elasticsearch clusters for performance, capacity, and reliability • Implement and improve observability through logging, metrics, tracing, and alerting infrastructure

 • Automate operational tasks and eliminate manual toil through scripting and tooling (Python, Bash, Go, etc.)

• Collaborate with development teams to optimize containerization strategies and deployment workflows

• Troubleshoot infrastructure issues, optimize resource utilization, and ensure system scalability

 • Contribute to security best practices including secrets management, network policies, and access controls

What You Bring Required:

 • 5+ years of experience in DevOps, Platform Engineering, or Infrastructure roles

 • Strong hands-on experience with Kubernetes in production environments (deployment, scaling, troubleshooting)

• Strong experience building and maintaining Jenkins pipelines, including writing custom Groovy pipeline code

 • Proficiency with infrastructure-as-code tools (Terraform, CloudFormation, or similar)

 • Experience with containerization technologies (Docker, container registries, image optimization)

• Solid scripting and automation skills (Groovy, Python, Bash, or Go)

 • Extensive hands-on experience with AWS cloud services (EC2, EKS, RDS, S3, IAM, VPC)

• Experience administering Elasticsearch clusters in production (indexing strategies, performance tuning, scaling)

• Strong understanding of Linux systems administration and networking fundamentals

 • Experience with monitoring and observability tools (Prometheus, Grafana, or equivalent) • Knowledge of Git workflows and version control best practices Preferred

 • Experience with Helm charts and Kubernetes operators

• Knowledge of secrets management solutions

 • Experience with logging aggregation systems (ELK stack, Fluentd)

• Background with microservices architectures and distributed systems

• Experience with Jenkins shared libraries and advanced pipeline patterns

• Knowledge of security best practices and compliance requirements (network policies, RBAC, pod security)

 • Experience with autoscaling strategies (HPA, VPA, Cluster Autoscaler, Karpenter)

• Understanding of NATS or other message queue systems

• Experience with data pipeline architectures and stream processing systems

 • Deep understanding of service networking, load balancing, and ingress controllers

 • Experience with cloud cost optimization and resource efficiency

• Previous experience mentoring junior engineers or leading technical initiatives Why Engineers Love Working at Radar

 • High impact — what you build directly drives customer value and product success

• Small team, big reach — startup-style ownership with enterprise stability

• Real engineering challenges — scaling a high-volume IoT platform is genuinely hard and deeply rewarding

#LI-NR1

 

Scheduled Weekly Hours:

40

 

About Radar BlackBerry Radar is a rapidly growing IoT platform that enables real-time tracking and analytics for thousands of trailers, containers, and high-value assets across North America. Learn more. Our platform has achieved strong market traction, with a fast-expanding device footprint and a lean, highly skilled engineering team tackling challenges in big data, cloud architecture, and performance optimization as adoption accelerates. Radar is at a critical inflection point. We’ve established product-market fit, our install base is scaling quickly, and our platform processes more data each month than ever before. We’re investing heavily in next-generation architecture to support the next five years of innovation and growth. Why This Role Matters Every new customer adds more devices, more data, and more opportunities to innovate. We’re expanding our engineering team to build the next generation of Radar’s cloud platform, focusing on:

• High-volume telemetry ingestion and big data pipelines

• Cloud re-architecture for scalability and resilience

• Advanced reporting and analytics

• API expansion and next-gen customer experiences

• Performance and reliability engineering

 • Modern DevOps tooling in a microservices environment Our Tech Stack

 • Backend: Node.js, Express, NATS

• Data: MySQL, Redis, Elasticsearch

• Analytics: Flink, Cube.js, StarRocks, Iceberg

• Cloud: AWS

• Frontend: React

• Platform: Docker, Kubernetes, ECS, Jenkins What You’ll Do

 • Design, deploy, and manage Kubernetes clusters and containerized workloads across development, staging, and production environments

• Build and maintain CI/CD pipelines using Jenkins for automated testing, building, and deployment of microservices

• Maintain and improve Jenkins infrastructure, shared libraries, and pipeline templates

 • Develop infrastructure-as-code using tools like Terraform and Helm to automate provisioning and configuration

• Create integrations between Kubernetes and internal systems (monitoring, logging, databases, etc.)

• Administer and optimize Elasticsearch clusters for performance, capacity, and reliability • Implement and improve observability through logging, metrics, tracing, and alerting infrastructure

 • Automate operational tasks and eliminate manual toil through scripting and tooling (Python, Bash, Go, etc.)

• Collaborate with development teams to optimize containerization strategies and deployment workflows

• Troubleshoot infrastructure issues, optimize resource utilization, and ensure system scalability

 • Contribute to security best practices including secrets management, network policies, and access controls

What You Bring Required:

 • 5+ years of experience in DevOps, Platform Engineering, or Infrastructure roles

 • Strong hands-on experience with Kubernetes in production environments (deployment, scaling, troubleshooting)

• Strong experience building and maintaining Jenkins pipelines, including writing custom Groovy pipeline code

 • Proficiency with infrastructure-as-code tools (Terraform, CloudFormation, or similar)

 • Experience with containerization technologies (Docker, container registries, image optimization)

• Solid scripting and automation skills (Groovy, Python, Bash, or Go)

 • Extensive hands-on experience with AWS cloud services (EC2, EKS, RDS, S3, IAM, VPC)

• Experience administering Elasticsearch clusters in production (indexing strategies, performance tuning, scaling)

• Strong understanding of Linux systems administration and networking fundamentals

 • Experience with monitoring and observability tools (Prometheus, Grafana, or equivalent) • Knowledge of Git workflows and version control best practices Preferred

 • Experience with Helm charts and Kubernetes operators

• Knowledge of secrets management solutions

 • Experience with logging aggregation systems (ELK stack, Fluentd)

• Background with microservices architectures and distributed systems

• Experience with Jenkins shared libraries and advanced pipeline patterns

• Knowledge of security best practices and compliance requirements (network policies, RBAC, pod security)

 • Experience with autoscaling strategies (HPA, VPA, Cluster Autoscaler, Karpenter)

• Understanding of NATS or other message queue systems

• Experience with data pipeline architectures and stream processing systems

 • Deep understanding of service networking, load balancing, and ingress controllers

 • Experience with cloud cost optimization and resource efficiency

• Previous experience mentoring junior engineers or leading technical initiatives Why Engineers Love Working at Radar

 • High impact — what you build directly drives customer value and product success

• Small team, big reach — startup-style ownership with enterprise stability

• Real engineering challenges — scaling a high-volume IoT platform is genuinely hard and deeply rewarding

#LI-NR1

 

Benefits:

The BlackBerry Employee Benefits programs offer a wide range of benefits that support your physical, financial and personal well-being. BlackBerry remains committed to offering affordable benefits including coverage for medical, dental, vision, life, disability insurance, retirement, employee share purchase program and paid-time-off to those that meet the eligibility requirements.

 

Disclosure of Position Status:

This job posting is part of a general recruitment effort without a guaranteed position

 

Disclosure of Artificial Intelligence:

We do not use artificial intelligence (AI) to screen, assess, or select applicants at any stage of our recruitment process. All applications are reviewed and evaluated by our hiring team.