Data Engineer (Data Platforms, Big Data)

Responsibilities

• Design, build, and maintain scalable cloud-native data platforms and Data Lakehouse solutions.
• Develop and optimise robust ETL/ELT pipelines for performance, reliability, and cost efficiency.
• Design end-to-end Data & AI solutions aligned with business and technical requirements.
• Implement automated data quality checks, monitoring, and data governance best practices.
• Build and manage cloud infrastructure using Infrastructure as Code (Terraform) and cloud-native services.
• Support cloud migration initiatives and modernise existing data platforms.
• Ensure platform security, scalability, and compliance with governance standards.
• Collaborate with business and technical stakeholders to translate requirements into technical solutions.
• Produce technical documentation and participate in architecture reviews.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or a related discipline.
• 3 years of experience in data engineering, data architecture, systems integration, or large-scale production data platforms.
• Strong hands-on experience with SQL, Python, Apache Spark, and ETL/ELT pipeline development.
• Experience with Apache Kafka, Apache Airflow, or similar orchestration and streaming technologies.
• Good understanding of cloud computing, distributed systems, containerisation, microservices, Infrastructure as Code, cloud security, and Identity & Access Management (IAM).
• Experience with DataOps, Data Lakehouse architectures, and exposure to MLOps or LLMOps.