Senior Software Engineer: Platform
Location: In office Calgary, Alberta
About BigGeo
BigGeo is redefining geospatial intelligence with an AI-ready Discrete Global Grid System (DGGS) that transforms how spatial data is captured, indexed, and monetized. Our platform powers mission-critical decisions across sectors where location intelligence drives outcomes—from large-scale infrastructure projects and environmental planning to logistics and emergency response. We are industry agnostic, unlocking possibilities for organizations that have yet to realize the value a system like ours can deliver.
Backed by Vivid Theory, a venture studio dedicated to building transformative technologies, we're a multidisciplinary, entrepreneurial team built for impact. We work quickly, push boundaries, and expect every team member to be both a thinker and a doer.
The Opportunity
We're seeking a Senior Platform Engineer focusing on high-performance backend systems using modern statically compiled languages. This role emphasizes building reliable, secure, and performant infrastructure that powers our product offerings. If you're a developer who thrives on creating high-performance, observable systems and isn't afraid to dive deep into low-level optimizations while building reliable platform services, we want to hear from you!
Primary Responsibilities
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Design and implement efficient, reliable, secure, and observable backend systems
- Optimize code for performance and resource utilization
- Contribute to architectural decisions for distributed systems and big-data processing
- Write and maintain observable, instrumented code that enables effective system monitoring
- Lead the development of complex platform features
- Design and implement scalable data architectures
- Conduct thorough performance testing and optimization
- Mentor junior developers, promote and enforce best practices
- Lead initiatives to align platform development with business objectives, ensuring that all platform functionalities contribute positively to key outcomes and KPIs
- Facilitate a smooth transition of platform features to product teams, supporting seamless integration and effective use within product pipelines
- Continuously evaluate and optimize the platform to enhance user experience and deliver measurable business value, supporting overall company growth objectives
- Assume full ownership and accountability for strategic technology domains, with the ability to articulate their business value and organizational impact
- Drive DevOps practices and automation initiatives
- Monitor and analyze technical performance of internal systems
- Leverage existing CI/CD pipelines and tooling for efficient deployment workflows
- Support deployment and operational excellence
- Contribute to infrastructure-as-code initiatives
Requirements
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Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field (or equivalent practical experience)
- Proven track record in high-performance backend development
- Proficiency in modern statically compiled languages
- Strong understanding of immutability principles and their application
- Expertise in writing efficient, reliable, and secure code
- Proficient with both manual memory management and automatic lifetime management techniques
- Strong understanding of computer architecture and efficient utilization of available resources
- Strong knowledge of fundamental data structures and algorithms
- Understanding of performance trade-offs between algorithmic efficiency, distributed systems coordination, and I/O minimization in big data contexts
- Experience with modern observability patterns and practices
Backend Technology Stack Requirements
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Core Languages & Frameworks
- Experience with modern statically compiled languages (Go, Rust, C++, or similar)
- Familiarity with testing frameworks and benchmarking tools
- Understanding of dependency management and build systems
- Databases & Data Storage
- Strong experience with relational databases (PostgreSQL, MySQL)
- Proficiency with NoSQL databases (MongoDB, Redis, Cassandra)
- Experience with time-series databases (InfluxDB, TimescaleDB, or Prometheus)
- Knowledge of database optimization, indexing strategies, and query performance tuning
- Experience with connection pooling and database driver optimization
- Message Queues & Event Streaming
- Experience with Apache Kafka, RabbitMQ, or NATS
- Understanding of event-driven architectures and pub/sub patterns
- Knowledge of message serialization formats (Protocol Buffers, Avro, MessagePack)
- APIs & Communication Protocols
- Expertise in RESTful API design and implementation
- Experience with gRPC and Protocol Buffers
- Knowledge of GraphQL is a plus
- Understanding of API versioning, rate limiting, and authentication patterns (OAuth2, JWT)
Container & Orchestration
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Proficiency with Docker and containerization best practices
- Experience with Kubernetes (deployment, scaling, service mesh)
- Knowledge of Helm charts and Kubernetes operators
- Experience with container registries and image optimization
- Cloud Platforms
- Hands-on experience with at least one major cloud provider (AWS, GCP, or Azure)
- AWS: ECS/EKS, Lambda, S3, RDS, ElastiCache, SQS/SNS
- GCP: GKE, Cloud Run, Cloud SQL, Pub/Sub, BigQuery
- Azure: AKS, Azure Functions, Cosmos DB, Service Bus
- Infrastructure as Code
- Experience with Terraform or Pulumi
- Knowledge of configuration management tools (Ansible, Chef, or similar)
- Experience with GitOps practices (ArgoCD, Flux)
CI/CD & DevOps Tools
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Experience working with CI/CD platforms (Jenkins, GitLab CI, GitHub Actions, CircleCI)
- Ability to effectively leverage existing CI/CD pipelines and deployment automation
- Knowledge of automated testing strategies (unit, integration, e2e)
- Familiarity with build processes and deployment workflows
- Observability & Monitoring
- Experience with Prometheus and Grafana
- Proficiency with distributed tracing (Jaeger, Zipkin, or OpenTelemetry)
- Knowledge of structured logging practices and tools
- Experience with APM tools (DataDog, New Relic, or Elastic APM)
- Understanding of SLIs, SLOs, and SLA definitions
- Version Control & Collaboration
- Expert-level Git proficiency
- Experience with code review processes and branching strategies
- Familiarity with monorepo or microservices repository patterns
Nice to Haves
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A Master's degree or relevant certifications in Distributed Systems, Big Data Processing, or Cloud Computing is a plus
- Experience with Rust (with tokio.rs) or Scala (with cats-effect) will be given top priority
- Experience with Go (Golang) including concurrency patterns, standard library, and popular frameworks
- Experience with any modern statically typed language (C++, Java, Kotlin)
- Background in big-data processing architectures (Spark, Flink, Hadoop)
- Experience with distributed systems and consensus algorithms (Raft, Paxos)
- Experience with high-performance data structures and lock-free programming
- Knowledge of geospatial data structures and algorithms (PostGIS, H3, S2 Geometry)
- Expertise in optimizing I/O operations and understanding of Linux kernel internals
- Familiarity with binary protocols and efficient serialization
- Experience with distributed eventing systems (e.g., NATS.io, Pulsar)
- Experience with service mesh technologies (Istio, Linkerd, Consul)
- Knowledge of caching strategies (Redis, Memcached, CDN optimization)
- Experience with load balancing and reverse proxy configuration (Nginx, HAProxy, Envoy)
- Familiarity with security best practices and compliance frameworks (SOC 2, GDPR, HIPAA)
- Experience with performance profiling tools (pprof, flamegraphs, perf)
- Knowledge of WebAssembly (Wasm) and its applications
- Contributions to open-source projects or maintaining libraries
- Experience with chaos engineering and resilience testing
- Passionate about code efficiency, reliability, and security
- Proactive in finding ways to improve existing systems
- Eager to learn, mentor and teach
- Strong problem-solving skills and critical thinking
- Excellent communication and teamwork abilities
Please visit http://biggeo.com for more information
