Data Pipeline Development: Design, construct, install, test, and maintain highly scalable data management systems. Ensure systems meet business requirements and industry practices.
Data Architecture Optimization: Build high-performance algorithms, prototypes, predictive models, and proof of concepts. Translate complex functional and technical requirements into detailed architecture, design, and high-performing software.
Data Integration and ETL Processes: Develop and maintain scalable ETL processes and pipelines to support data collection, integration, and transformation across various sources and formats.
Database Management: Administer, monitor, and manage database systems to ensure security, quality, and integrity of data. Implement measures to improve data reliability, efficiency, and quality.
Collaboration with Analytics Teams: Work closely with analytics and business teams to assist with data-related technical issues and support their data infrastructure needs.
Performance Tuning: Monitor analytics and data processing systems' performance, tuning and scaling systems as needed to ensure optimal performance and cost-effectiveness.
Data Security and Compliance: Implement secure coding practices, encryption, and other measures to protect sensitive data. Ensure compliance with data governance and privacy regulations.
Emerging Technologies Exploration: Research and implement best practices in data engineering, staying informed of new technologies and tools that can enhance data accuracy and insights.

Data Engineer

US (Remote)