GRADUATE DATA ENGINEER

JOB SUMMARY Raras Technologies PLC is seeking ten enthusiastic, analytical, and highly motivated Graduate Data Engineers who are passionate about data, programming, and solving complex problems through technology. The successful candidates will support the design, development, testing, and maintenance of data pipelines and integration solutions that collect, process, transform, validate, and deliver reliable data from diverse sources. They will work with databases, programming languages, data integration tools, and modern data processing technologies to support enterprise applications, analytics, reporting, and data-driven decision-making. This position is designed for individuals at the beginning of their professional careers who demonstrate strong technical aptitude, a willingness to learn, and the determination to develop practical expertise in data engineering. Candidates will receive opportunities for hands-on learning, technical mentorship, and collaborative problem-solving and progressive responsibility. No prior professional experience is required. Candidates will be assessed primarily on their foundational knowledge, problem-solving ability, learning agility, initiative, and passion for building a career in data engineering. KEY RESPONSIBILITIES A. Data Engineering and Integration Assist in developing, testing, and maintaining data pipelines to collect data from databases, enterprise applications, APIs, files, and other sources. Support the extraction, transformation, and loading of data using appropriate ETL/ELT techniques. Help develop data ingestion workflows for batch and, where applicable, real-time data processing. Assist in integrating data from different systems and formats into centralized data platforms. Troubleshoot data pipeline errors and contribute to improving the reliability and efficiency of data integration processes. B. Data Processing and Transformation Write and maintain SQL queries and Python scripts to extract, clean, transform, and process data. Support data profiling, standardization, deduplication, and preparation for downstream use. Assist in implementing data processing logic using suitable programming frameworks and tools. Apply appropriate data structures, schemas, formats, and storage practices. Contribute to the development of reusable, maintainable, and efficient data processing workflows. C. Data Quality and Validation Perform data quality checks to assess accuracy, completeness, consistency, and validity. Assist with source-to-target data reconciliation and investigate discrepancies. Identify missing values, duplicate records, inconsistent formats, and other data anomalies. Document validation results, testing activities, and identified issues. Work with team members to resolve data quality problems and improve the reliability of data outputs. D. Databases and Data Platforms Work with relational databases and develop an understanding of database structures, schemas, and query execution. Learn and apply concepts relating to data warehouses, data lakes, and modern data lakehouse architectures. Assist with data loading, storage organization, query optimization, and data retrieval. Support the monitoring and troubleshooting of data processing jobs and workflows. Develop an understanding of distributed data processing, data storage formats, and large-scale data management. E. Technical Documentation and Collaboration Prepare and maintain technical documentation, data mappings, workflow descriptions, and testing records. Collaborate with senior engineers, software developers, database administrators, analysts, and other technical stakeholders. Participate in technical discussions, code reviews, knowledge-sharing sessions, and assigned learning activities. Follow established coding standards, version control practices, testing procedures, and documentation guidelines. Continuously improve technical skills and progressively take ownership of assigned tasks.