Data Engineer

Skills: Python, Snowflake, Big Data, Azure, Data Modeling, ETL/ELT processes, PySpark, SQL, Qualifications And Skills Proficiency in Python, SQL, and Snowflake (Mandatory skill) for developing robust data solutions. Expertise in working with big data frameworks and technologies for managing and processing large datasets. Experience with Microsoft Azure for cloud-based data storage and processing solutions. Strong understanding of data modeling principles to design efficient and scalable data architectures. Hands-on experience with ETL and ELT processes to ensure seamless data integration and transformation. Proficiency in PySpark for distributed data processing and analysis across large datasets. Solid problem-solving skills with the ability to troubleshoot complex data-related issues effectively. Excellent communication skills to collaborate with cross-functional teams and stakeholders efficiently. Roles And Responsibilities Design, construct, and maintain scalable data pipelines to support various business needs and analytics. Collaborate with data scientists and analysts to understand data requirements and deliver suitable solutions. Optimize and monitor data workflows to ensure high performance and reliability of data systems. Work with engineering teams to integrate data solutions seamlessly with existing systems and applications. Implement best practices in data management, including data quality, integrity, and security measures. Stay updated with industry trends and advancements to continually improve data engineering processes. Deliver data-driven insights and recommendations to drive strategic business decisions. Troubleshoot and resolve data-related issues promptly to maintain system integrity and performance. Show more Show less