About the Role
Our client is a dynamic, technology-driven organisation operating across a broad range of disciplines, including cloud technologies, data management and processing, embedded systems, electronics, software and hardware engineering, product design and manufacturing, artificial intelligence, computer vision, and advanced analytics. These capabilities support the development and operation of complex digital products and platforms.
They are seeking a Data Engineer with strong experience in data modelling, database technologies, and data pipeline development. In this role, you will help maintain and enhance existing systems while contributing to the design and implementation of new features with a focus on performance, scalability, and reliability. You will collaborate closely with software engineering and data teams to deliver robust, efficient, and maintainable solutions.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines using modern data orchestration and processing technologies.
- Create and optimise data models that support evolving business requirements and application functionality.
- Develop and maintain database queries, stored procedures, and other data-layer components to support internal services and applications.
- Troubleshoot, maintain, and enhance existing systems to improve reliability, performance, and maintainability.
- Design and execute automated testing strategies, including unit and integration tests, to ensure solution quality.
- Monitor, profile, and optimise system performance to support scalability and responsiveness under varying workloads.
- Produce and maintain clear technical documentation covering data architecture, workflows, and codebases.
- Collaborate with multidisciplinary engineering teams to deliver integrated, end-to-end solutions.
- Continuously learn and adopt new technologies, tools, and best practices while contributing across a range of technical initiatives as required.
Requirements
- Degree in Computer Science, Software Engineering, Data Engineering, or a related discipline, or equivalent commercial experience in data platform and pipeline development.
- Practical experience with workflow orchestration and scheduling tools such as Dagster, Airflow, or similar platforms.
- Strong knowledge of relational database systems and SQL, with experience designing and optimising database solutions.
- Proficiency in Python and object-oriented programming principles.
- Experience designing and implementing data models for both operational and analytical workloads.
- Strong analytical, debugging, troubleshooting, and performance optimisation capabilities.
- Experience using version control systems such as Git, including participation in collaborative development and code review processes.
- Excellent communication and interpersonal skills, with the ability to work effectively in cross-functional teams.
- A pragmatic approach to solution design, balancing custom-built capabilities with established third-party technologies to deliver reliable and scalable systems.
- Experience working with continuous integration and continuous deployment (CI/CD) practices and associated automation tools.
- Understanding of API design and integration principles, including REST, GraphQL, or comparable service architectures.
- Comfortable working within Linux-based development and deployment environments.
- Familiarity with containerisation and orchestration technologies such as Docker, Kubernetes, or equivalent platforms.
- Knowledge of software engineering best practices, including Test-Driven Development (TDD), automated testing frameworks, and common software design patterns.
