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 .