Join our team as a Data Engineer and take the lead in architecting and implementing robust data solutions. This role involves the end-to-end lifecycle of data generation, collection, and processing. You will be instrumental in building efficient data pipelines, ensuring exceptional data quality, and executing ETL processes for seamless data migration and deployment across systems.

As a Data Engineer, your daily activities will focus on designing, developing, and maintaining comprehensive data solutions that underpin data generation, collection, and processing. You will be key in establishing efficient data pipelines for smooth data flow. Maintaining data accuracy and quality is paramount, alongside implementing effective ETL processes to support data migration and deployment, ultimately reinforcing the organization's data infrastructure and analytical capabilities.

Independently contribute to projects, aiming to become a subject matter expert. Actively participate and contribute to team discussions, offering solutions to challenges. Collaborate with cross-functional teams to define data requirements and deliver scalable solutions. Monitor and optimize data workflows for enhanced performance and reliability. Document data processes thoroughly and maintain clear stakeholder communication. Support junior team members through knowledge sharing and guidance.

Demonstrated proficiency in Apache Hadoop is essential. Experience with distributed computing frameworks and big data processing is required. A strong understanding of data storage architectures and data modeling is necessary. Familiarity with data pipeline orchestration and workflow management tools is beneficial. The ability to efficiently troubleshoot and resolve data processing issues is critical. Knowledge of data security and governance best practices is expected. A minimum of 3 years of experience in Apache Hadoop is mandatory. A 15-year full-time education is a prerequisite for this role.