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.