- 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
- 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
- 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
- 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
- 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
- A Master's degree or relevant certifications in Distributed Systems, Big Data Processing, or Cloud Computing is a plus
- Experience with Rust (with ) 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., , 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
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Senior Software Engineer: Platform - Calgary - Biggeo
Description
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
Requirements
Nice to Haves
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