Data Engineer #IFL

Data Management & Transformation

• Design, develop, and maintain scalable data pipelines integrating data from a variety of business applications, databases, and external sources.
• Implement data quality controls and validation processes to ensure data accuracy, consistency, completeness, and reliability.
• Perform data transformation, cleansing, aggregation, filtering, and enrichment to support business and analytical requirements.
• Establish and maintain appropriate governance practices for data, analytical models, and automated decision-making processes.
• Develop and maintain logical and physical data models, including data structures, relationships, and business rules.
• Ensure data platforms and solutions adhere to relevant security, governance, and compliance standards.

Platform Optimisation & Automation

• Develop and maintain automated deployment and integration processes for data solutions and cloud-based infrastructure.
• Optimise data pipelines, processing workflows, and data models for performance, scalability, reliability, and cost efficiency.
• Monitor and optimise data processing and storage capacity, including capacity planning and forecasting.
• Identify and resolve system and query performance issues through appropriate tuning, optimisation, caching, indexing, and other techniques.
• Monitor platform utilisation and implement appropriate housekeeping and cost-management practices.
• Support the deployment, integration, and ongoing operation of advanced analytics and AI/ML solutions within the data platform.
• Continuously assess and improve the reliability, maintainability, and operational efficiency of the data environment.

Collaboration & Stakeholder Engagement

• Work closely with data leads, technology teams, and business stakeholders to establish and manage data as a strategic business asset.
• Translate business requirements into scalable and sustainable data solutions.
• Provide guidance to business users on the development and maintenance of reports, dashboards, and analytical solutions.
• Promote good data management, governance, and engineering practices across relevant stakeholder groups.

Job Requirements

• Bachelor's degree in Computer Science, Data Science, Software Engineering, Information Systems, or another relevant quantitative or technical discipline. A Master's degree is advantageous.
• At least 10 years of relevant experience in data engineering, data management, data integration, data modelling, data quality, data platform optimisation, or related disciplines.
• Strong experience designing and implementing modern cloud-based data architectures and data platforms.
• Strong programming skills in Python and SQL. Experience with distributed data processing frameworks is highly desirable.
• Experience working with both relational and non-relational databases. Familiarity with enterprise or legacy database technologies is advantageous.
• Experience with software engineering and DevOps practices, including source control, CI/CD, automated deployment, and workflow orchestration.
• Experience with data governance, metadata management, data cataloguing, and access-control frameworks.
• Familiarity with business intelligence and data visualisation tools is advantageous.
• Experience supporting the deployment and operationalisation of AI/ML solutions, including areas such as feature engineering and production inference, is desirable.
• Strong understanding of data security, governance, scalability, performance, and operational best practices.
• Strong analytical, problem-solving, communication, and stakeholder management skills.