Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable data pipelines to support business intelligence, analytics, and operational reporting.

• Build and optimise ETL/ELT processes to integrate structured and unstructured data from multiple internal and external data sources.

• Develop and maintain data models, data warehouses, and data lakes to support enterprise data management.

• Ensure data quality, integrity, security, and governance across the organisation's data platforms.

• Collaborate with software engineering, product, analytics, and business stakeholders to understand data requirements and deliver reliable data solutions.

• Monitor, troubleshoot, and optimise data pipeline performance to ensure high availability and scalability.

• Implement data validation, monitoring, and automation processes to improve operational efficiency.

• Support cloud-based data platform initiatives and contribute to data architecture improvements and technology enhancements.

• Prepare technical documentation, data dictionaries, and operational procedures for data engineering solutions.

• Stay current with emerging technologies and recommend improvements to enhance the organisation's data capabilities.

Required Skills & Experience

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related discipline.

• At least 10 years of experience in data engineering, data integration, or related technical roles.

• Strong experience designing and maintaining ETL/ELT pipelines and enterprise data solutions.

• Proficiency in SQL and programming languages such as Python, Java, or Scala.

• Experience with relational and NoSQL databases, data warehousing concepts, and cloud-based data platforms.

• Familiarity with big data technologies and modern data engineering frameworks.

• Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues.

• Good understanding of data governance, security, and data quality best practices.

• Strong communication and stakeholder management skills with the ability to work effectively in cross-functional teams.

Nice to Have

• Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.

• Experience with Apache Spark, Kafka, Airflow, or similar data engineering technologies.

• Knowledge of DevOps, CI/CD, and infrastructure automation practices.

• Experience supporting AI, machine learning, or advanced analytics initiatives.

• Experience working in financial services, fintech, insurance, or technology organisations.