Data Engineer (Hybrid) -AOS

We are seeking a skilled Data Engineer (Hybrid) with approximately 3 years of experience to join our team. The ideal candidate will be proficient in Python and capable of designing, building, and maintaining scalable data pipelines and architectures. This role involves working in a hybrid environment, combining onsite and remote work, to support data integration, transformation, and analytics initiatives that drive business decisions.

• Design, develop, and maintain efficient and scalable data pipelines using Python and other relevant technologies.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver robust data solutions.
• Implement ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes.
• Monitor data quality and troubleshoot data-related issues to ensure data integrity and reliability.
• Optimize data workflows and storage for performance and cost-effectiveness.
• Maintain documentation related to data engineering processes, architectures, and systems.
• Stay updated with emerging data engineering tools and technologies to continuously improve data infrastructure.

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• At least 3 years of professional experience in data engineering or a related role.
• Strong proficiency in Python programming for data processing and automation.
• Experience with ETL tools and data pipeline orchestration frameworks.
• Familiarity with relational and NoSQL databases, data warehousing solutions, and cloud platforms is a plus.
• Good understanding of data modeling, data architecture, and data governance principles.
• Ability to work effectively in a hybrid work environment, balancing onsite collaboration with remote tasks.
• Strong problem-solving skills and attention to detail.

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