Data Enginer

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.QualificationsBachelor’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.Good written and verbal communication skills in English.