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Key Responsibilities and Required Skills for Backend Software Engineer

💰 $ - $

Software EngineeringBackendEngineeringCloud

🎯 Role Definition

As a Backend Software Engineer you will design, build, and operate the server-side systems that power our products. You will be responsible for creating scalable, maintainable, and secure APIs and services, collaborating closely with product, frontend, and infrastructure teams. This role requires deep technical ownership, a strong understanding of distributed systems, and a track record of delivering production-grade features in cloud-native environments. Keywords: Backend Software Engineer, microservices, RESTful APIs, gRPC, scalable systems, AWS/GCP/Azure, Docker, Kubernetes, CI/CD, observability.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Backend Engineer or Software Engineer I
  • Full-Stack Developer looking to focus on backend systems
  • Site Reliability Engineer or DevOps Engineer transitioning to product teams

Advancement To:

  • Senior Backend Engineer / Senior Software Engineer
  • Tech Lead or Engineering Manager
  • Staff Engineer / Principal Engineer
  • Solutions Architect or Platform Engineer

Lateral Moves:

  • Site Reliability Engineering (SRE)
  • Data Engineer / Data Platform Engineer
  • DevOps or Cloud Infrastructure Engineer

Core Responsibilities

Primary Functions

  • Architect, design, and implement scalable, maintainable backend services and microservices using best practices for modularity, testability, and performance to support millions of daily requests.
  • Design and develop RESTful APIs and/or gRPC services with clear versioning, authentication (OAuth2/JWT), and documentation (OpenAPI/Swagger) to enable secure, predictable integrations for frontend and third-party clients.
  • Build and optimize data models and storage layouts for both relational databases (PostgreSQL, MySQL) and NoSQL systems (MongoDB, DynamoDB, Cassandra) to meet latency, consistency, and throughput requirements.
  • Implement event-driven architectures and asynchronous processing using message brokers (Kafka, RabbitMQ, AWS SQS) to decouple services and enable robust background processing and stream processing pipelines.
  • Lead performance tuning and capacity planning efforts, including query optimization, indexing strategies, caching (Redis, Memcached), and end-to-end profiling to reduce latency and increase system throughput.
  • Own and maintain CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, CircleCI) to automate builds, tests, deployments, and rollbacks for frequent, low-risk releases to staging and production.
  • Design and deploy cloud-native infrastructure and services using IaaC tools (Terraform, CloudFormation) and managed cloud services (AWS, GCP, Azure) to ensure reliable, cost-effective operations.
  • Implement containerization strategies (Docker) and orchestrate microservices on Kubernetes (EKS/GKE/AKS) including Helm charts, readiness/liveness probes, and autoscaling policies.
  • Ensure observability across services by implementing structured logging, distributed tracing (OpenTelemetry, Jaeger), metrics (Prometheus, Grafana), and alerting to facilitate rapid incident detection and root-cause analysis.
  • Develop and enforce security best practices across the backend stack, including input validation, secure secret management, role-based access controls, encryption in transit & at rest, and regular dependency security scanning.
  • Write clear, thorough unit, integration, and end-to-end tests and champion test-driven development (TDD) practices to guarantee reliability and maintainability of core systems.
  • Participate actively in architecture reviews, design discussions, and code reviews to raise the bar on code quality, maintainability, and architectural consistency across teams.
  • Implement feature toggles and canary/blue-green deployment strategies to minimize risk during rollout of new functionality and enable rapid rollback when necessary.
  • Collaborate closely with product managers and frontend engineers to translate product requirements into technical specifications, breaking down complex features into deliverable engineering tasks.
  • Take ownership of service-level objectives (SLOs), service-level indicators (SLIs), and error budgets; drive improvements to meet reliability goals and participate in on-call rotations to respond to production incidents.
  • Drive data migration and schema evolution strategies, including zero-downtime migrations and backward-compatible changes to support continuous delivery.
  • Mentor and coach junior engineers, providing feedback on design, performance tuning, and coding practices; help hire and onboard new backend engineers to the team.
  • Maintain and improve developer experience by building internal tools, CLI utilities, and automated scaffolding to accelerate service creation and standardize engineering practices.
  • Conduct load testing and chaos engineering experiments to validate system resilience under adverse conditions and to surface weak points before they impact customers.
  • Analyze and reduce technical debt by prioritizing refactors, modularizing monoliths into services when appropriate, and documenting known limitations and follow-up work.
  • Collaborate with data engineering and analytics teams to expose backend metrics and events in a way that enables robust product analytics and business reporting.
  • Research and evaluate new backend technologies, frameworks, and libraries; produce prototypes and present tradeoffs to leadership to inform long-term technology choices.
  • Ensure high-quality technical documentation for APIs, libraries, operational runbooks, and architectural decisions for both internal and external stakeholders.
  • Drive continuous process improvements in Agile ceremonies (sprint planning, retrospectives), contributing to better predictability and delivery velocity for backend roadmap items.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Participate in incident postmortems and implement action items to prevent recurrence.
  • Provide technical input on security audits and compliance efforts (SOC2, GDPR, HIPAA where applicable).
  • Serve as an internal advocate for backend best practices, API design, and performance budgets.

Required Skills & Competencies

Hard Skills (Technical)

  • Programming languages: Strong proficiency in one or more backend languages such as Java, Kotlin, Go, Python, Node.js (TypeScript/JavaScript), or C#.
  • API design: Experience designing and documenting RESTful APIs, gRPC endpoints, and GraphQL services with a focus on backward compatibility and versioning.
  • Databases: Deep experience with relational databases (Postgres, MySQL) and at least one NoSQL store (Redis, MongoDB, DynamoDB) including schema design and query optimization.
  • Distributed systems: Solid understanding of microservices architecture, service discovery, circuit breakers, rate limiting, and eventual consistency patterns.
  • Messaging & streaming: Hands-on experience with Kafka, RabbitMQ, or cloud messaging services for event-driven designs and real-time processing.
  • Cloud platforms: Production experience deploying and operating services on AWS, GCP, or Azure along with managed services (RDS, ECS/EKS, Cloud SQL).
  • Containers & orchestration: Docker and Kubernetes experience including building images, health checks, deployments, and scaling strategies.
  • CI/CD & automation: Familiarity with pipeline tools (GitHub Actions, Jenkins, GitLab CI) and infrastructure-as-code (Terraform, CloudFormation).
  • Observability & monitoring: Implementing logs, metrics, and distributed tracing using tools like Prometheus, Grafana, ELK/EFK, Datadog, and OpenTelemetry.
  • Security & authentication: Knowledge of OAuth2, JWT, TLS, secure secret management, and dependency vulnerability scanning (Snyk, Dependabot).
  • Testing & quality: Experience with unit testing frameworks, integration tests, contract testing, and test automation to ensure robust releases.
  • Performance engineering: Profiling, benchmarking, and optimizing code paths; experience with load testing tools such as JMeter, k6, or Locust.
  • Infrastructure knowledge: Familiarity with networking fundamentals, DNS, load balancers, and CDN integration for distribution and scaling.

Soft Skills

  • Strong communication skills to translate technical concepts to product managers, stakeholders, and cross-functional teams.
  • Problem-solving mindset with a bias for action and ownership over delivered outcomes.
  • Collaboration and teamwork: experience working in cross-functional agile teams and contributing positively to team dynamics.
  • Mentorship: ability to coach junior engineers and provide constructive feedback during code reviews.
  • Time management: capability to prioritize work against roadmap goals, support critical incidents, and manage multiple concurrent projects.
  • Adaptability: willingness to evaluate new technologies and change course when better solutions are identified.
  • Analytical thinking: data-driven decision-making approach and comfort interpreting telemetry to drive product and infrastructure decisions.
  • Customer empathy: focus on delivering a reliable, performant user experience and understanding downstream impacts of technical choices.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.

Preferred Education:

  • Master's degree in Computer Science or related discipline, or advanced coursework in distributed systems, databases, or cloud computing.
  • Professional certifications (AWS Certified Solutions Architect, Google Professional Cloud Developer, Certified Kubernetes Application Developer) are a plus.

Relevant Fields of Study:

  • Computer Science
  • Software Engineering
  • Computer Engineering
  • Information Systems
  • Applied Mathematics

Experience Requirements

Typical Experience Range:

  • 3–7 years of professional backend development experience for mid-level roles; 7+ years for senior/lead roles.

Preferred:

  • 5+ years building and operating production backend systems, experience with cloud-native architectures, microservices, and distributed computing.
  • Proven track record of launching large-scale features, improving reliability (SLO/SLI), and mentoring engineers.
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