Gather, analyse, and document business and data requirements.
Enhance data collection and consumption processes through more efficient data integration channels.
Design, develop, and maintain data pipelines, ETL processes, and reporting solutions to support analytics and business needs.
Prepare test plans, execute system testing, and support user acceptance testing (UAT).
Collaborate with technical and business stakeholders to ensure successful deployment and adoption of solutions.
Monitor, support, and maintain production systems to ensure service reliability and performance.
Troubleshoot and resolve data, application, and infrastructure-related issues.
Requirements
5-7 years of experience with Python, PySpark, Linux, SQL, data modelling, and ETL tools such as Informatica.
Experience with Hadoop ecosystem technologies such as Hive, Impala, and Cloudera Data Platform (CDP) is advantageous
Good understanding of data warehousing, analytics platforms, and large-scale data processing.
Experience delivering projects using Agile and/or Waterfall methodologies
Familiarity with reporting and visualisation tools such as Tableau and SAP BusinessObjects.
Experience with data virtualisation platforms such as Denodo and DevOps practices is preferred.
Strong problem-solving skills with the ability to diagnose issues across infrastructure, data, and application layers.
Experience designing and supporting highly available, secure, and high-performance systems in on-premises, data centre, or hybrid cloud environments is an advantage.
