Role DescriptionWe are seeking a technically capable and analytical Data Engineer to design, develop, and maintain reliable data infrastructure and pipelines. The role involves transforming raw data into high-quality, accessible datasets that support business intelligence, analytics, reporting, and data-driven decision-making.

Key responsibilities include

- Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
- Collect, integrate, transform, and validate data from multiple internal and external sources.
- Develop and optimize data models, databases, data warehouses, and data processing workflows.
- Ensure data accuracy, consistency, availability, and reliability across data platforms.
- Monitor data pipelines and troubleshoot data quality, performance, and integration issues.
- Collaborate with data analysts, data scientists, software engineers, and business stakeholders to understand data requirements.
- Implement data quality checks, validation processes, and appropriate governance practices.
- Optimize queries, pipelines, and data processing solutions for performance and scalability.
- Maintain clear technical documentation for data architecture, pipelines, processes, and datasets.
- Support the implementation of cloud-based data platforms and modern data engineering technologies.




- Contribute to continuous improvements in data architecture, engineering standards, and development practices.

Qualifications
- Bachelor’s degree or above in Computer Science, Data Engineering, Information Technology, Mathematics, Engineering, or a related discipline.
- Strong understanding of data structures, databases, data modeling, ETL/ELT, and data engineering principles.
- Proficiency in SQL and familiarity with one or more programming languages such as Python, Java, or Scala.
- Familiarity with relational and non-relational databases, data warehouses, and distributed data processing technologies.
- Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud is an advantage.
- Familiarity with data pipeline, orchestration, and version-control tools such as Airflow, dbt, Git, or similar technologies.
- Strong analytical, troubleshooting, and problem-solving skills.
- Understanding of data quality, security, governance, and privacy principles.
- Ability to work collaboratively with technical and non-technical stakeholders.
- Strong attention to detail and commitment to data accuracy and reliability.
- Valuable written and verbal communication skills in English.

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