Data Engineer

A Data Engineer is responsible for designing, implementing, and maintaining data pipelines and architectures for collecting, processing, and storing data. They work closely with data scientists and analysts to ensure data is accessible and ready for analysis. The role involves developing and optimizing ETL processes, managing data infrastructure, and ensuring data quality and integrity. Data Engineers also research and implement new technologies and tools to enhance data processing capabilities.

Key Responsibilities:

• Design and implement scalable data pipelines to process large volumes of data efficiently.
• Collaborate with cross-functional teams to understand data requirements and deliver solutions.
• Optimize data storage and retrieval processes for better performance.
• Ensure data quality by implementing data validation and monitoring processes.
• Develop and maintain data architecture for analytics and reporting purposes.
• Work on data modeling and schema design to support business needs.
• Troubleshoot data-related issues and provide timely resolutions.
• Stay updated on industry trends and best practices in data engineering.
• Document data pipelines, processes, and solutions for future reference.
• Collaborate with data scientists to deploy machine learning models in production.

Qualifications:

• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• Proven experience in building and optimizing data pipelines for large-scale data processing.
• Proficiency in programming languages such as Python, SQL, or Java.
• Strong understanding of data warehousing concepts and technologies.
• Experience with cloud platforms like AWS, GCP, or Azure for data storage and processing.