Data Engineer

Introduction

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G – Grow in accelerated development path

L – Lead yourself with purpose & commitment

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W – Way Forward

Our comprehensive one-year program is tailored to empower talented and driven graduates like you with valuable hands-on experience, exposure to industry experts, and a diverse range of projects that will sharpen your skills and broaden your understanding to the ICT industry.

Data Engineer

As part of our data-driven transformation initiatives, we are looking for a motivated Associate Data Engineer to join our team. This role is ideal for early-career professionals who are passionate about building scalable data pipelines, integrating diverse data sources, and enabling intelligent applications through robust data infrastructure.

Responsibilities

• Assist in designing, developing, and maintaining data pipelines and ETL/ELT processes to support application and analytics needs.
• Collaborate with software developers and integration teams to ensure seamless data flow between systems and applications.
• Work with structured and unstructured data from APIs, databases, and third-party platforms.
• Support the implementation of data models, data warehouses, and data lakes for enterprise clients.
• Ensure data quality, consistency, and security across all stages of the data lifecycle.
• Participate in performance tuning, monitoring, and troubleshooting of data workflows.
• Document data engineering processes, schemas, and integration logic.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• Internship or academic project experience in data engineering, data integration, or database development is a plus.
• Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server).
• Familiarity with data pipeline tools and frameworks such as Apache Airflow, dbt, or similar.
• Experience with Python or another scripting language for data manipulation.
• Understanding of ETL/ELT concepts and data warehousing principles.
• Exposure to cloud data services (e.g., AWS Glue, Azure Data Factory, Google BigQuery) is a plus.
• Knowledge of APIs, JSON, and data integration techniques.
• Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server).
• Familiarity with data pipeline tools and frameworks such as Apache Airflow, dbt, or similar.
• Experience with Python or another scripting language for data manipulation.
• Understanding of ETL/ELT concepts and data warehousing principles.
• Exposure to cloud data services (e.g., AWS Glue, Azure Data Factory, Google BigQuery) is a plus.
• Knowledge of APIs, JSON, and data integration techniques.