- Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software.
- Apply data mining, data modelling, natural language processing, and machine learning to extract and analyse information from large structured and unstructured datasets.
Requirements:
· Bachelor's degree in Computer Science, Information Technology, or a related field
· Proven experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments
· Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)
· Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes
· Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java
· Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
· Experience with Graphana, Prometheus, Splunk will be an added benefit
· Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges
· Excellent collaboration and communication skills to work effectively with cross-functional teams
· Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment
· Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus
