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Key Responsibilities and Required Skills for Backend Engineer

💰 $90,000 - $160,000

EngineeringBackendSoftware DevelopmentCloud

🎯 Role Definition

We are seeking a pragmatic, systems-minded Backend Engineer to design, build, and operate highly available, low-latency backend systems and APIs. This role focuses on building scalable microservices, designing reliable data models, optimizing performance, and ensuring security and observability across production services. The successful candidate will collaborate closely with Product, Frontend, DevOps, and Data teams to deliver end-to-end solutions, mentor junior engineers, and drive technical decisions that improve velocity and reliability.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Backend Developer / Software Engineer I
  • DevOps Engineer with strong application experience
  • Full-Stack Developer transitioning to backend specialization

Advancement To:

  • Senior Backend Engineer / Staff Backend Engineer
  • Tech Lead / Engineering Manager
  • Principal Engineer / Architect

Lateral Moves:

  • Site Reliability Engineer (SRE)
  • Data Engineer
  • Full-Stack Engineer

Core Responsibilities

Primary Functions

  • Design, implement, and maintain robust, scalable RESTful and GraphQL APIs and microservices using modern backend frameworks (e.g., Spring Boot, Express, Django, FastAPI, Go net/http), ensuring clear contracts and versioning strategies.
  • Architect and develop distributed systems that handle high throughput and low latency, including partitioning, sharding, and replication strategies for data stores.
  • Build and maintain data models, schema migrations, and query optimization for relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB) databases to meet performance and consistency goals.
  • Implement and optimize caching layers (Redis, Memcached, CDNs) and design cache invalidation strategies to reduce latency and database load.
  • Design and implement reliable event-driven architectures using message brokers and streaming platforms (Kafka, RabbitMQ, AWS SNS/SQS), ensuring durable, ordered, and idempotent processing.
  • Build production-grade authentication and authorization mechanisms (OAuth2, JWT, role-based access control) and enforce secure coding practices to protect data and APIs.
  • Design and own CI/CD pipelines for automated build, test, and deployment processes (GitHub Actions, Jenkins, CircleCI), including blue/green and canary deployment patterns and rollback strategies.
  • Containerize services and manage orchestration with Docker and Kubernetes, including health checks, probes, resource requests/limits, and autoscaling policies.
  • Implement observability: structured logging, distributed tracing (OpenTelemetry, Jaeger), and application/infra metrics (Prometheus, Grafana) to provide actionable insights and SLIs/SLOs.
  • Profile and optimize application performance, identify bottlenecks, and implement improvements across code paths, database access, and infrastructure.
  • Write comprehensive unit, integration, contract and end-to-end tests (JUnit, pytest, Mocha, Postman) and maintain high automated test coverage to reduce regression risk.
  • Maintain and improve API documentation, developer portals, and internal SDKs to accelerate partner and frontend integrations.
  • Collaborate with product managers and stakeholders to refine requirements, scope features, estimate work, and deliver timely, high-quality backend solutions.
  • Lead code reviews, mentor junior engineers, and promote best practices in architecture, coding standards, and testability.
  • Design fault-tolerant systems with graceful degradation, retries, timeouts, circuit breakers, and bulkheads to improve availability under failure.
  • Implement infrastructure as code (Terraform, CloudFormation) to provision, manage, and version cloud resources for repeatability and auditability.
  • Ensure service reliability through capacity planning, load testing (locust, k6), incident response playbooks, and on-call rotations.
  • Integrate with third-party APIs and partner systems, manage API contracts, handle rate limiting and exponential backoff, and ensure secure data exchange.
  • Reduce technical debt by identifying refactoring opportunities, improving modularity, and driving backwards-compatible migrations that minimize customer impact.
  • Drive backend architecture decisions: monolith-to-microservices migrations, data ownership, service decomposition, and cross-team API contracts.
  • Ensure compliance with data protection and privacy requirements (GDPR, CCPA) by implementing correct data retention, anonymization, and encryption-at-rest/in-transit practices.
  • Participate in performance and security reviews with SRE and Security teams, and remediate vulnerabilities and risks in a timely manner.
  • Monitor production incidents, lead post-mortems, document root causes and action items, and implement safeguards to prevent recurrence.
  • Collaborate with Data Engineering and Analytics teams to provide clean, reliable event and metric streams for reporting, ML models, and business intelligence.
  • Drive continuous improvement by introducing new tools, libraries, design patterns, and processes that increase engineering productivity and product quality.

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.

Required Skills & Competencies

Hard Skills (Technical)

  • Strong proficiency in at least one backend language: Java/Kotlin, Go, Python, or Node.js (TypeScript/JavaScript), with production experience.
  • Deep experience building RESTful and/or GraphQL APIs, including API design, versioning, and documentation (OpenAPI/Swagger).
  • Expertise with relational databases (PostgreSQL, MySQL) and experience in writing efficient SQL, indexing strategies, and ACID considerations.
  • Experience with NoSQL databases (MongoDB, DynamoDB, Cassandra) and understanding trade-offs between consistency, availability, and partition tolerance.
  • Hands-on experience with message brokers and streaming platforms: Apache Kafka, RabbitMQ, AWS SQS/SNS, including at-least-once/exactly-once semantics.
  • Practical knowledge of containerization (Docker) and container orchestration (Kubernetes), including deployments, service meshes, and Helm charts.
  • Experience with cloud platforms (AWS, GCP, or Azure) and core services: compute, storage, networking, IAM, managed databases, and serverless (Lambda, Cloud Functions).
  • Familiarity with CI/CD tooling and pipeline automation: GitOps, GitHub Actions, Jenkins, CircleCI, or similar.
  • Observability and monitoring experience: Prometheus, Grafana, ELK/EFK stack, OpenTelemetry, and distributed tracing tools.
  • Proficiency in testing strategies: unit, integration, contract testing, and test automation frameworks relevant to your stack.
  • Infrastructure as Code experience: Terraform, CloudFormation, or Pulumi for reproducible environment provisioning.
  • Performance engineering skills: profiling, load testing (k6, locust), and capacity planning.
  • Security fundamentals: OAuth2, JWT, TLS, encryption at rest, secrets management, and common OWASP mitigations.
  • Experience with caching strategies and systems (Redis, Memcached) and CDN integration.
  • Familiarity with build tools, package managers, and dependency management for the chosen technology stack.
  • Knowledge of design patterns for distributed systems, including CQRS, event sourcing, and idempotency patterns.
  • Experience integrating third-party APIs and handling rate limits, backoffs, and retries.
  • Comfortable with Linux-based server environments and basic networking concepts (TCP/IP, HTTP/2, TLS).
  • Strong code review, refactoring, and technical documentation practices.

Soft Skills

  • Strong communication skills: translate complex technical decisions to non-technical stakeholders and write clear documentation.
  • Problem-solving mindset: diagnose root causes and propose pragmatic, measurable solutions.
  • Ownership and accountability: take end-to-end responsibility for features in production.
  • Collaboration: work effectively across product, frontend, QA, SRE, and Data teams.
  • Mentorship: coach junior engineers, lead design reviews, and lift engineering quality.
  • Time management and prioritization: balance urgent production issues with long-term technical initiatives.
  • Continuous learning: proactively stay current with backend engineering trends, tools, and best practices.
  • Customer-focused orientation: understand how backend decisions impact user experience and business metrics.
  • Adaptability: thrive in fast-paced environments and handle shifting priorities.
  • Attention to detail: deliver reliable, well-tested, and maintainable code.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.

Preferred Education:

  • Master's degree in Computer Science, Software Engineering, or related technical field, or equivalent professional certifications (e.g., cloud certifications).

Relevant Fields of Study:

  • Computer Science
  • Software Engineering
  • Information Systems
  • Electrical Engineering
  • Applied Mathematics / Statistics

Experience Requirements

Typical Experience Range:

  • 3–7+ years of professional backend engineering experience (adjustable by seniority level).

Preferred:

  • 5+ years for Senior roles; proven track record building production microservices at scale, owning services end-to-end, and leading technical initiatives. Experience in cloud-native architectures (AWS/GCP/Azure), event-driven systems, and strong operational maturity (on-call, monitoring, incident management).
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