Data Engineering

Key ResponsibilitiesDesign, 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 RequirementsBachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Technology or a related discipline.Minimum 4–5 years of hands-on experience in data engineering, software development, application engineering or related technical functions.Proficiency in at least one programming language, preferably Python, Java or TypeScript.Strong SQL skills, including complex querying, data transformation, performance tuning and optimisation.Practical experience developing and maintaining ETL/ELT pipelines, data models and system integrations.Experience working with REST APIs, scripting and workflow automation.Hands-on experience with Power BI or comparable business intelligence and reporting tools.Familiarity with cloud environments, ideally Microsoft Azure, and cloud-based data processing services.Knowledge of modern software development practices, including Git, CI/CD and deployment automation.Experience implementing technical solutions across the full development lifecycle.Additional Technical AdvantagesPractical experience with Databricks, including data transformation, processing and pipeline development.Exposure to AI/ML applications, predictive modelling, Generative AI or LLM-based solutions.Experience with Azure data services, cloud-native architectures or distributed data processing.Familiarity with enterprise application integrations, SaaS platforms and workflow orchestration tools.Relevant technical certifications in Microsoft Azure, Databricks or related data engineering technologies.