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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

• 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

• 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

Nice to Haves

• 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