Design, develop and maintain robust ETL/ELT pipelines to support data ingestion, transformation and integration across multiple systems. Build and optimise SQL queries, data models and database structures to improve data processing efficiency and performance. Develop applications, automation scripts and integration solutions using Python, Java, TypeScript or other relevant programming languages.
Implement API integrations and automated workflows to connect internal applications, databases and external platforms. Develop and maintain data visualisation solutions and interactive dashboards using Power BI or equivalent technologies. Work with cloud-based data platforms, preferably Microsoft Azure and Databricks, to support scalable data processing and analytics.
Participate in the technical design, development, testing and deployment of data engineering and automation solutions. Explore and implement AI-enabled capabilities, including predictive analytics, intelligent automation and Large Language Model (LLM) applications. Integrate third-party SaaS platforms and enterprise applications with existing technology environments.
Apply software engineering best practices, including version control, CI/CD, testing, technical documentation and performance optimisation. Troubleshoot data quality issues, pipeline failures, integration errors and application performance bottlenecks. Technical
Bachelor's degree in Computer Science, Software Engineering, Da