Please mention DailyRemote when applying
We are seeking a skilled and passionate Senior Backend Engineer to join our team, focusing on the design, development, and maintenance of high-performance, scalable microservices. The ideal candidate will have strong expertise in Go (Golang), and a deep understanding of distributed systems architecture.
|
Skill Category |
Requirement |
Proficiency Level |
|---|---|---|
|
Programming Languages |
Python (Deep expertise with frameworks like FastAPI, Flask, or Django) |
Advanced |
|
Go (Golang) (Experience building robust, high-concurrency microservices) |
Expert |
|
|
Microservices/Architecture |
Designing, developing, and deploying RESTful APIs |
Expert |
|
Security |
Keycloak, API authentication, JWT |
Advanced |
|
Databases |
Realtime analytics (Clickhouse) |
Advanced |
|
Relational databases (MySQL) including complex query optimization. |
Advanced |
|
|
NoSQL databases (Redis). |
Advanced |
|
|
Containerization/Orchestration
|
Kubernetes for deployment and scaling. Docker container build |
Advanced Advanced |
|
Testing |
Writing comprehensive unit, integration, and end-to-end tests. |
Advanced |
7+ years of professional experience in backend software development, with a significant focus on building and operating microservices in a production environment.
Proven ability to work with and contribute to large-scale, distributed systems.
Experience with cloud platforms (AWS, Azure, or GCP) for deployment, monitoring, and scaling.
CI/CD: Experience setting up and maintaining automated deployment pipelines
Observability: Proficiency with monitoring and logging tools
Source Control: Expertise in Git and collaborative workflows
Familiarity with event-driven architectures and streaming data processing.
Experience with security best practices in API design (e.g., OAuth 2.0, JWT, input validation).
Knowledge of performance tuning and optimization techniques for both Python and Go applications.
Design, implement, and maintain scalable and reliable backend microservices using Go.
Collaborate with product managers and front-end teams to define API specifications and integration points.
Ensure services are deployed, monitored, and scaled efficiently in a Kubernetes environment.
Participate in code reviews, design discussions, and planning sessions.
Troubleshoot and resolve complex production issues, ensuring high availability and performance.
Drive continuous improvement in development processes, tooling, and infrastructure.
Has owned at least 1–2 services end-to-end (design → build → deploy → on-call → incident fixes → scaling)
Comfortable with service boundaries, APIs, versioning, backward compatibility, SLAs/SLOs
Can design systems with tradeoffs: latency, throughput, cost, reliability
Patterns: idempotency, retries, timeouts, circuit breakers, async workflows, queues, eventual consistency
Data design: relational vs NoSQL, caching, indexing, migrations, multi-tenant considerations (if relevant)
Can take an ambiguous production issue and drive it to resolution
Uses a structured approach: reproduce → isolate → instrument → hypothesis → validate → fix → prevent
Confident with commands/tools like: ps/top/htop, journalctl, systemctl, netstat/ss, lsof, curl, grep/sed/awk, strace (bonus), log parsing
Understands networking basics (DNS, TLS, ports, timeouts)
Can explain Dockerfiles, layers, multi-stage builds, image size/security
Debug containers: env vars, volumes, entrypoints, networking, resource limits
Strong in structured logging, correlation IDs, trace context
Metrics + tracing + logs as a system
Datadog experience is a must-have , or a very credible equivalent (Prometheus/Grafana + OpenTelemetry + ELK) with proof they can ramp fast
CI/CD, release processes, rollback strategies
Basic security and reliability hygiene (secrets mgmt, least privilege, rate limiting)
$140,000 – $200,000 USD per year (depending on experience and qualifications)
401(k) retirement plan
Health, dental, and vision insurance
Paid time off (PTO) and company holidays
Flexible work arrangements
Professional development and training support
Performance-based bonuses (if applicable)
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