Data Engineer

Role Overview The Data Engineer plays a crucial role in designing, building, and maintaining the data infrastructure that enables reliable analytics, reporting, and data-driven decision-making. This position focuses on developing scalable data pipelines, ensuring data accuracy, and optimizing data systems across the organization. Working closely with data analysts, data scientists, and software engineers, the Data Engineer ensures that high-quality data is accessible, secure, and ready for use in advanced business and technical applications. Key Responsibilities Design, build, and maintain robust data pipelines and ETL/ELT workflows to support operational and analytical needs. Develop and optimize data architectures, including data lakes, data warehouses, and real-time processing solutions. Ensure data quality, data consistency, and proper data validation across all systems. Collaborate with cross-functional teams to understand data requirements, integrate new data sources, and support strategic initiatives. Monitor system performance, troubleshoot data pipeline issues, and implement improvements for scalability and efficiency. Manage and maintain metadata, data catalogs, and documentation to support data governance. Implement data security best practices and support compliance with internal policies and industry standards. Automate workflows and optimize data processes to reduce manual effort and increase reliability. Participate in code reviews, contribute to architecture discussions, and uphold engineering best practices. Support analytics and AI/ML teams by ensuring reliable access to clean, organized, and well-structured data assets. Qualifications and Requirements Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field. 3–5 years of experience in data engineering, data integration, or backend development. Strong proficiency in building data pipelines, ETL/ELT processes, and working with both structured and unstructured data. Hands‑on experience with relational and NoSQL databases, data modeling, and query optimization. Familiarity with distributed data processing frameworks and modern data engineering tools. Proficiency in at least one programming language commonly used in data engineering. Solid understanding of data warehousing concepts, workflow orchestration, and cloud-based data infrastructure. Strong analytical and problem-solving skills, with attention to detail and reliability. Ability to work collaboratively in a fast‑paced environment and manage multiple priorities. Strong documentation, communication, and cross-team collaboration abilities. Summary The Data Engineer is a key contributor to building a reliable and scalable data environment that supports analytical excellence and business intelligence. This role requires a blend of technical expertise, problem-solving skills, and a commitment to delivering high‑quality data solutions that empower organizational growth and innovation. #J-18808-Ljbffr