Data Engineering

Key Responsibilities

• 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 Requirements

• Bachelor'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 Advantages

• Practical 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.