Senior Backend Engineer ((Python / Go)

Job description

--- # **Senior Backend Engineer (Python / Go)** ## **Overview** 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. --- ## **Essential Qualifications** ### **Technical Skills** | Skill Category | Requirement | Proficiency Level | | --- | --- | --- | | Programming Languages | Python (Deep expertise with frameworks like FastAPI, Flask, or Django) | Advanced | | Programming Languages | 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 | | Databases | Relational databases (MySQL) including complex query optimization | Advanced | | Databases | NoSQL databases (Redis) | Advanced | | Containerization / Orchestration | Kubernetes for deployment and scaling | Advanced | | Containerization / Orchestration | Docker container build | 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 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)** ### **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 ### **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) ### **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 ### **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) ### **Docker + container runtime competence** - Can explain Dockerfiles, layers, multi-stage builds, image size/security - Debug containers: env vars, volumes, entrypoints, networking, resource limits ### **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 ### **Platform maturity** - CI/CD, release processes, rollback strategies - Basic security and reliability hygiene (secrets mgmt, least privilege, rate limiting) --- ## **Compensation** ### **Compensation & Benefits** $140,000 – $200,000 USD per year (depending on experience and qualifications) ### **Benefits** - 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)