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.
MINIMUM QUALIFICATIONS
Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Information Systems, Data Science, Mathematics, or Related fields .
Zero years of professional experience required. Recent graduates and candidates entering the data engineering profession are encouraged to apply.
Basic understanding of programming concepts and logical problem-solving.
Foundational knowledge of SQL and relational databases.
Basic familiarity with Python or another programming language.
Understanding of fundamental data concepts, including tables, schemas, data types, and common data formats.
Willingness to learn new technologies, participate in practical training, and work collaboratively in a technical environment.
Relevant academic projects, personal projects, internships, online courses, bootcamps, and self-directed learning are advantages but are not mandatory where candidates demonstrate strong aptitude and commitment.
TECHNICAL KNOWLEDGE AND SKILLS
Candidates should demonstrate foundational knowledge in the following areas or a strong willingness and ability to develop these skills.
Programming and Databases
SQL fundamentals, including filtering, joins, aggregation, and basic query optimization.
Python fundamentals, including variables, functions, loops, data structures, and error handling.
Basic relational database concepts and familiarity with database connectivity.
Data Engineering Fundamentals
Understanding of data pipelines and ETL/ELT processes.
Familiarity with structured, semi-structured, and unstructured data.
Basic knowledge of CSV, JSON, and other common data formats.
Awareness of data cleansing, validation, transformation, and data quality principles.
Data Processing Technologies
Basic awareness of distributed computing and big data processing concepts.
Familiarity with Apache Spark or similar data processing frameworks is an advantage.
Awareness of data ingestion and integration tools, such as Apache NiFi.
Basic understanding of data storage technologies and formats, such as Parquet and ORC.
Familiarity with data warehouses, data lakes, and lakehouse concepts.
Development and Operating Environments
Basic familiarity with Linux commands and command-line environments.
Awareness of Git and version control.
Understanding of software testing, debugging, and technical documentation.
Familiarity with workflow scheduling, automation, or data pipeline monitoring is an advantage.
Candidates are not expected to have hands-on experience with every technology listed. The ability to understand technical concepts, learn independently, and apply knowledge to practical problems is particularly important.
CORE COMPETENCIES AND PERSONAL ATTRIBUTES
Passion for data engineering: Demonstrates genuine interest in data, programming, technology, and continuous professional development.
Analytical thinking: Can break down problems, identify patterns, and develop logical solutions.
Learning agility: Learns new concepts quickly and applies feedback to improve performance.
Initiative and self-discipline: Takes responsibility for learning, completing assigned tasks, and improving technical capabilities.
Attention to detail: Understands the importance of accuracy, consistency, and reliability in data processing.
Problem-solving and persistence: Approaches technical challenges methodically and is willing to investigate unfamiliar problems.
Teamwork and communication: Collaborates effectively, asks relevant questions, shares knowledge, and communicates technical findings clearly.
Professional integrity: Demonstrates accountability and respects confidentiality, information security, and organizational policies.
Requirement Skill
Big Data tools
Basic Data/Record-keeping.
Data Collection & Analysis
Desired Skill
Data visualization & pattern-finding through critical thinking
Data visualisation
How To Apply
Interested applicants should submit an updated CV to hm310852@gmail.com highlighting their educational background, relevant technical knowledge, academic or personal projects, and any applicable training or certifications.
Please include the position you are applying for in the email subject line.
Shortlisted candidates may be invited to complete a technical assessment and participate in an interview covering basic SQL, programming logic, data concepts, analytical thinking, and problem-solving.
Raras Technologies PLC welcomes ambitious graduates who are eager to learn, gain practical experience, and build a long-term career in data engineering.
