As a Data Engineer, you will design, develop, and maintain scalable data infrastructure that supports business intelligence, analytics, and data-driven decision-making. The role involves building reliable data pipelines, integrating data from multiple sources, optimizing database performance, and ensuring the availability, quality, and security of enterprise data. You will collaborate with cross-functional teams to understand business requirements, develop efficient data solutions, and deliver structured datasets that support reporting, advanced analytics, and operational initiatives. Responsibilities include designing data architectures, implementing ETL and ELT processes, monitoring data workflows, validating data integrity, troubleshooting performance issues, automating data processing tasks, and maintaining technical documentation. You will also contribute to data governance initiatives, improve data management practices, and implement best practices for scalability, reliability, and security. This position offers the opportunity to work with modern cloud technologies, databases, and data platforms while driving innovation, operational efficiency, and business growth through high-quality data solutions. Qualifications Candidates should possess strong analytical, logical, and problem-solving skills, with the ability to design and optimize scalable data solutions. A solid understanding of databases, data modeling, SQL, ETL processes, and distributed data systems is highly valued. Familiarity with programming languages used for data engineering, cloud-based data platforms, workflow automation, API integration, and data warehousing concepts is beneficial. The ideal applicant is detail-oriented, adaptable, and capable of managing multiple priorities while maintaining high standards of accuracy and reliability. Excellent communication and collaboration skills are essential for working effectively with technical and non-technical stakeholders. Applicants should demonstrate curiosity, accountability, continuous learning, and a commitment to improving data quality and operational efficiency. The ability to solve complex technical challenges and contribute to scalable, secure, and efficient data infrastructure will be key to success in this role.