Aws Data Engineer

Responsibilities:

• Develop, implement, and maintain efficient and scalable data engineering solutions to support the company's data initiatives.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical data engineering solutions.
• Build and maintain data pipelines to ingest, transform, and store data from various sources, ensuring data quality, integrity, and reliability.
• Deploy and operationalize machine learning models for real-time inference and prediction on edge devices.
• Optimize data processing workflows to achieve high performance and low latency in handling large volumes of data.
• Design and implement data warehouse and data lake solutions to support data analytics and reporting needs.
• Collaborate with data scientists and data analysts to understand their data requirements and assist in the design and implementation of data solutions.
• Monitor and troubleshoot data pipelines, proactively addressing any performance issues, bottlenecks, or failures to ensure uninterrupted data flow.
• Stay updated with industry trends and emerging technologies in data engineering, edge computing, cloud services, data warehousing, and data lakes, and evaluate their potential for improving existing systems and processes.
• Continuously improve data engineering processes and systems through the adoption of best practices and innovative approaches.

Skills and Qualifications:

Mandatory

• Bachelors or masters degree in computer science, Data Engineering, or a related field.
• 1-2 years of experience as a Data Engineer, with expertise in developing scalable data solutions.
• Strong experience in data engineering, including data ingestion, transformation, storage, and data pipeline optimization.
• Proficiency in programming languages such as Python, Java, SQL for data engineering and analytics tasks.