Developer (Junior) at Discovery Limited

Key Purpose

• The Junior Developer supports the development, operationalisation, reliability, and continuous improvement of software platform, and AI/ML solutions, and data products. The role focuses on translating technical requirements into high-quality, maintainable code, while supporting the deployment, monitoring, and ongoing maintenance of machine learning pipelines and platform services. The role bridges development and operations by contributing to platform engineering, DevOps, and service management, ensuring that AI solutions are effectively delivered and sustained in production environments. This includes ensuring that systems are stable, scalable, production-ready, efficiently deployed through CI/CD pipelines, continuously improved, and aligned with business requirements and technical standards

Key outputs

The successful applicant will be responsible for but not limited to the following job functions:

Areas of responsibility may include but not limited to

Software Development & Test Automation

• Collaborate with Data Scientists, Architects, Analysts, and Platform teams to implement technical specifications using appropriate development languages (primarily Python and SQL) in alignment with established engineering standards and architectural patterns
• Develop high-quality, production-grade source code that adheres to DHS technical standards, leveraging existing system components, exposed services, and reusable sub-processes
• Build and maintain Python-based utilities and scripts to support operational workflows, including: Data quality checks and validation, log parsing and analysis, and automation of repetitive support and maintenance tasks
• Write and optimise SQL queries within Google Cloud Platform (GCP) environments to support production investigations, root cause analysis, data validation and reconciliation, ad hoc analysis and issue diagnosis
• Design, implement, and maintain automated testing frameworks, including unit tests, integration tests, end-to-end (E2E) testing for pipelines and services, and test data management
• Contribute to code quality, security, and compliance practices, including static analysis, linting, and secure coding standards
• Maintain and enhance technical documentation for: system and architecture documentation, code-level documentation, development guidelines, database schemas, structure updates, and rule changes
• Update and manage work items in Agile/DevOps tooling (e.g., Jira), ensuring traceability of changes and alignment to delivery processes
• Participate in pair programming, code reviews, and knowledge-sharing activities to promote best practices and continuous team development
• Support ongoing refactoring and optimisation of existing codebases to improve performance, scalability, and maintainability

Continuous Integration & Continuous Delivery (CI/CD)

• Contribute to CI/CD pipelines for automated build, test, and deployment processes
• Assist in managing configurations and environment setup
• Work with cloud platforms (primarily GCP) and containerised environments
• Support release processes with a focus on stability and zero-defect delivery
• Monitor pipeline health and troubleshoot failed builds or deployments
• Continuously build skills in cloud, DevOps, and AI/ML technologies

Platform Engineering & Operations Support

• Execute production deployments and verify the post-release health, stability, availability and responsiveness of deployed services
• Participate in the process of reviewing code for consistent application of standards, logic and effective use of libraries and reusable aspects of the application.
• Find and report operational issues and execute configuration changes
• Coordinate with multiple platform teams to monitor system resources,
• Manage platform services alerts and respond to incidents escalated by the Incidents team.
• Conduct Root Cause Analysis (RCAs) for bugs, defects and other types of problems (including writing clear and concise incident reports and communications)
• Log issues in the appropriate issues tracking system.
• Conduct analysis on issues.
• Verify and validate build stability.
• Conduct end-to-end testing and fix any defects found.
• Review error logs and provide updates on fixes found in testing.
• Monitor CI/CI and AI/ML pipelines, diagnosing failed builds and deployments
• Understand the relationship between pipeline stages, environments, and production deployments, and retrigger rollbacks
• Maintain awareness of all pipeline components
• Participate in on-call rotations for IT Service Management and incident response and support

Personal Attributes and Skills

The successful candidate would need to have the following competencies:

Behavioural skills

• Strong learning orientation with a willingness to continuously build technical and domain knowledge
• Structured and analytical approach to problem solving and debugging
• Effective prioritisation, planning, and organisation of tasks
• Ability to work under pressure and manage competing deadlines
• Proactive, action-oriented mindset with a collaborative approach to teamwork

Core Technical Skills

• Programming: Python (primary) and SQL, with the ability to write clean, efficient, and production-ready code for data processing, automation, and backend services
• Computer Science Foundations: Solid understanding of data structures, algorithms, and software design principles, with exposure to object-oriented and functional programming concepts
• Data & Databases: Basic knowledge of relational databases (PostgreSQL, MySQL, SQLite), including data modelling fundamentals, and data validation
• Version Control & CI/CD: Practical experience with Git-based workflows (branching, pull requests, code reviews)
• Comfortable working in Linux/Unix environments, using command-line tools, shell scripting, and debugging application and pipeline issues via logs and monitoring tools

Advantageous Skills (Nice to Have)

• Exposure to application development paradigms, including microservices, monolithic, or full-stack/web applications (e.g., FastAPI, Django, React, Next.js)
• Familiarity with CI/CD pipelines and release processes (e.g., GitHub Actions, GitLab CI, Jenkins, Cloud Build), including automated testing, build validation, and deployment workflows
• Exposure to cloud-native and data platforms, including containerisation (Docker), orchestration concepts (Kubernetes, Helm), and data pipeline or workflow tooling
• Exposure to observability and monitoring tools (e.g., Datadog, Dynatrace, New Relic), including working with logs, metrics, and alerts for debugging and performance monitoring
• Familiarity with AI/ML ecosystems and tooling, including: Basic ML concepts and model lifecycle (training, evaluation, deployment), LLM platforms and tooling (e.g., OpenAI, Anthropic, Hugging Face, RAG concepts), and agentic and workflow frameworks (e.g., LangChain, LangGraph, n8n, crew.ai)

Education and Experience

The following requirements are Essential:

• Matric with Mathematics and English
• Relevant tertiary qualification (e.g., Computer Science, Information Systems, Data Science, or similar)
• Up to 1 year of experience in software development or related practical exposure (internships, projects)
• Foundational understanding of:  SDLC and basic testing practices, database design concepts and relational data structures, version control and technical processes, and working knowledge of Python and SQL (PostgreSQL, SQLite, or similar relational databases advantageous)