Microservice Backend Engineer (Python/Go)
Microservice Backend Engineer (Python/Go)
Citizenship: U.S. citizenship required due to federal contract requirements
(No active security clearance needed at time of hire)
Overview
We are seeking a skilled and passionate 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 both Python and Go (Golang), and a deep understanding of distributed systems architecture.
Essential Qualifications
Technical Skills
|
Skill Category |
Requirement |
Proficiency Level |
|---|---|---|
|
Programming Languages |
Python (Deep expertise with frameworks like FastAPI, Flask, or Django) |
Expert |
|
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. |
Advanced |
|
Testing |
Writing comprehensive unit, integration, and end-to-end tests. |
Advanced |
Core Experience
-
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.
Desired Qualifications
Process & Tools
-
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
Architecture & Design
-
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.
Key Responsibilities
-
Design, implement, and maintain scalable and reliable backend microservices using Python and 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.
Must-have skills for a Senior Backend / Microservices Engineer (owner-level)
1) Production microservices ownership (not just “worked on”)
-
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
2) System design & architecture (senior bar)
-
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)
3) Strong debugging & problem-solving in real-world scenarios
-
Can take an ambiguous production issue and drive it to resolution
-
Uses a structured approach: reproduce → isolate → instrument → hypothesis → validate → fix → prevent
4) Linux fundamentals (practical, daily-use)
-
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)
5) Docker + container runtime competence
-
Can explain Dockerfiles, layers, multi-stage builds, image size/security
-
Debug containers: env vars, volumes, entrypoints, networking, resource limits
6) Observability / logging / diagnostics
-
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
7) Platform maturity
-
CI/CD, release processes, rollback strategies
-
Basic security and reliability hygiene (secrets mgmt, least privilege, rate limiting)
Coding in Python - senior architecture + prod ops + observability.
Salary: $120,000 to $200,000 Per Year
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