Full stack Developer Backend (GCB4) Role Summary We are seeking an engineer with strong expertise in both API development and database development, capable of designing, implementing and maintaining reliable, scalable solutions across both areas. Key Responsibilities Backend (API) Engineer Responsibilities

• Design, develop and maintain scalable backend services, APIs and integration components, including database procedures and functions where required.
• Contribute to system and solution architecture, ensuring services are scalable, reliable and maintainable.
• Implement secure-by-design practices, including authentication, authorisation, data protection and secure coding.
• Write clean, maintainable and well-tested code; participate in code reviews and uphold engineering standards.
• Profile, monitor and tune backend services to maintain performance, availability and resilience.
• Troubleshoot production issues, conduct root-cause analysis and implement preventative improvements.
• Collaborate with frontend engineers, product managers, QA, platform/SRE teams and other stakeholders to deliver end-to-end solutions.
• Document APIs, services, integration patterns and operational runbooks to support maintainability and knowledge transfer.

Database and Data Engineering Responsibilities

• Design, develop and maintain ETL pipelines and data-ingestion processes from sources such as data lakes, files and databases.
• Design and optimise data models, schemas, database queries and storage strategies for operational, analytical and machine-learning use cases.
• Build and maintain data lakes, warehouses and other data platforms, ensuring scalability, performance and cost efficiency.
• Implement batch and real-time data processing solutions, with appropriate controls for performance, resilience and operational cost.
• Establish data-quality, lineage, observability and monitoring capabilities across data pipelines and platforms.
• Own or contribute to CI/CD, infrastructure-as-code and automated deployment practices for data services.
• Troubleshoot data-platform and pipeline issues, perform capacity planning and implement preventative improvements.
• Ensure data solutions meet applicable security, compliance and governance requirements.
• Collaborate with business partners, solution architects, subject-matter experts, analysts and source-system teams to translate requirements into production-ready data solutions.
• Produce technical documentation and lead knowledge-transfer sessions for data models, pipelines, platforms and operational processes. Required Skills & Experience Backend (API) Engineer – Required Skills
• Strong backend engineering fundamentals, including data structures, algorithms, concurrency and distributed-systems concepts.
• Experience designing, building and maintaining server-side applications and APIs, including RESTful and/or event-driven architectures.
• Strong understanding of API design, integration patterns, authentication, authorisation and secure coding practices.
• Experience with relational databases, including PostgreSQL, SQL, indexing, transactions and data consistency.
• Ability to design scalable systems that support high throughput, reliability and large volumes of operational workloads.
• Practical experience with unit and integration testing, version control and CI/CD practices.
• Strong debugging, problem-solving and root-cause-analysis skills.
• Language-agnostic mindset, with proficiency in one or more of the following: Python, Java, C++, C#, Clojure, CoffeeScript, F#, JavaScript, Go, Ruby, Rust, TypeScript or Scala.
• Ability to communicate technical concepts clearly and collaborate effectively with frontend engineers, product teams, QA, platform/SRE teams and other stakeholders.

Database and Data Engineer – Required Skills

• Strong SQL expertise, including query development, optimisation, joins, indexing, transactions and stored procedures.
• Experience with relational and columnar data stores, such as PostgreSQL, Oracle and Microsoft SQL Server.
• Practical experience designing data models, schemas and storage structures for operational, analytical and/or machine-learning use cases.
• Proficiency in Python, Java or C# for data processing, automation and scripting.
• Experience developing and supporting ETL/ELT pipelines and batch or real-time data-processing solutions.
• Experience with data-orchestration tools such as Apache Airflow, Prefect or Azure Data Factory.
• Knowledge of data-modelling and architecture tools, such as Visual Paradigm.
• Understanding of data quality, lineage, observability, monitoring and governance practices.
• Strong debugging, performance-tuning, capacity-planning and automation skills, with awareness of processing efficiency and cost optimisation.
• Experience with CI/CD, automated deployments and infrastructure-as-code for data services.
• Good stakeholder communication and technical-documentation skills, with the ability to work with business partners, architects, analysts, subject-matter experts and source-system teams.