Back End Developer

Key Responsibilities

Backend Development and Architecture

• Design, develop, and maintain backend services and APIs using Go (Golang).
• Build scalable, distributed, and event-driven systems capable of handling thousands of transactions per second.
• Design service interfaces, data flows, and integration patterns that support independent deployment, horizontal scaling, and future growth.
• Apply sound software design principles, appropriate abstractions, and proven architectural patterns without introducing unnecessary complexity.
• Identify and resolve performance bottlenecks, concurrency issues, and resource constraints.

AWS Cloud Infrastructure and Dynamic Scaling

• Develop and deploy production services on AWS using appropriate computer, networking, storage, and managed service offerings.
• Implement horizontally scalable services that dynamically adjust capacity in response to changing traffic and processing demand.
• Deploy and operate containerized workloads using Kubernetes.
• Configure and optimize autoscaling, resource allocation, health checks, and service recovery.
• Apply infrastructure-as-code and automated deployment practices to ensure repeatable, consistent environments.
• Consider performance, availability, security, and cloud operating costs when making engineering decisions.

Event Processing and Data Management

• Build asynchronous, event-driven processing pipelines using Apache Kafka.
• Design reliable message producers and consumers, including appropriate handling of retries, duplicate messages, ordering, and processing failures.
• Design and optimize relational database schemas, SQL queries, indexes, transactions, and data migrations.
• Design, develop, and optimize NoSQL data models using Couchbase, ensuring efficient data access, high throughput, scalability, and performance in distributed systems.
• Understand data consistency, concurrency, transaction boundaries, and the trade-offs between relational and NoSQL storage.
• Ensure data integrity and resilience across distributed services.

Quality, Reliability, and Production Operations

• Write clean, maintainable, well-documented code supported by automated unit, integration, and appropriate end-to-end tests.
• Participate constructively in code reviews, design reviews, and technical discussions.
• Instrument services with meaningful logs, metrics, traces, dashboards, and actionable alerts.
• Troubleshoot production issues through systematic investigation and root-cause analysis.
• Design for failure, including dependency outages, traffic spikes, timeouts, partial failures, and message-processing errors.
• Participate in production support and incident response as appropriate for the team.
• Continuously improve service performance, reliability, security, and maintainability.

Engineering Collaboration and Ownership

• Translate business and product requirements into practical technical designs and deliverable work.
• Own assigned features and services from initial design through implementation, deployment, and ongoing operation.
• Communicate technical decisions, risks, dependencies, and trade-offs clearly.
• Collaborate with other engineers, product stakeholders, and infrastructure teams.
• Contribute to engineering standards and help improve development practices across the team.

Required Qualifications

• Minimum 3 years of professional software engineering experience building and operating production backend systems in an AWS or comparable cloud-native environment.
• Strong, hands-on proficiency in Go (Golang) for production backend development.
• Demonstrated experience designing, building, and operating services handling thousands of transactions per second, with the ability to explain how throughput and performance were measured.
• Practical experience implementing dynamic scaling and horizontal scaling for production workloads.
• Hands-on experience deploying and operating containerized applications using Kubernetes.
• Practical experience with Apache Kafka, including producers, consumers, topics, partitions, consumer groups, and failure handling.
• Hands-on experience with relational databases (RDBMS) and NoSQL databases, specifically Couchbase, including data modelling, querying, indexing, and performance optimization.
• Strong understanding of RESTful APIs, service integration, concurrency, and distributed systems fundamentals.
• Experience with automated testing, version control, code reviews, and CI/CD pipelines.
• Understanding of production monitoring, troubleshooting, performance optimization, and service reliability.
• Strong problem-solving skills, sound technical judgment, and the ability to work independently while collaborating effectively with a team.

Preferred Qualifications

• Experience with AWS services such as EKS, EC2, ECS, Lambda, S3, RDS, DynamoDB, SQS, or related services, as relevant to the architecture.
• Experience with Infrastructure as Code using Terraform, AWS CDK, or CloudFormation.
• Familiarity with Docker, Helm, Kubernetes autoscaling, and resource management.
• Experience with observability tools such as Prometheus, Grafana, OpenTelemetry, or CloudWatch.
• Understanding of distributed system reliability patterns, including idempotency, backpressure, circuit breakers, rate limiting, and graceful degradation.
• Experience with load testing, capacity planning, latency analysis, and performance profiling.
• Knowledge of cloud security fundamentals, including IAM, least-privilege access, secrets management, encryption, and secure API design.
• Experience optimizing cloud infrastructure for cost and operational efficiency.

Engineering Standards and Expectations

• Ownership: Take responsibility for delivering working software and maintaining its production health, not just completing assigned coding tasks.
• Technical depth: Understand why a solution works, its limitations, and how it behaves under load and failure.
• Quality by design: Treat automated testing, code review, security, and observability as standard parts of development.
• Evidence-based decisions: Use measurements, benchmarks, logs, and production data to validate assumptions and diagnose problems.
• Pragmatic architecture: Choose solutions that meet current requirements while allowing for sensible future growth; avoid both premature optimization and avoidable technical debt.
• Continuous improvement: Learn from incidents, feedback, code reviews, and new technologies, and turn those lessons into better engineering practices.
• Clear communication: Explain technical decisions and trade-offs in language appropriate for both technical and nontechnical stakeholders.

Education

• A bachelor’s degree in computer science, Software Engineering, or a related field is preferred. Equivalent professional experience and demonstrated technical ability are acceptable.
• Measures of Success
• Deliver reliable backend features that meet agreed requirements and delivery commitments.
• Build and maintain services that sustain target throughput and latency under representative workloads.
• Demonstrate effective scaling behavior as traffic and processing demand increase.
• Maintain appropriate automated test coverage and production observability.
• Diagnose and resolve issues efficiently, with lasting improvements following significant incidents.
• Produce readable, maintainable code and contribute positively to team engineering standards.
• Make sound technical decisions that balance delivery speed, reliability, maintainability, security, and cost.