Data Engineering Lead

Requirements

1. Lead and manage a team of data engineers, providing guidance, mentorship, and technical expertise.
2. Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and translate them into effective data engineering solutions.
3. Design, develop, and maintain scalable and robust data pipelines to ingest, process, transform, and store large volumes of data from diverse sources.
4. Architect and optimize data warehouses and databases for performance, reliability, and scalability.
5. Ensure data quality, integrity, and security throughout the data lifecycle by implementing appropriate validation, cleansing, and encryption techniques.
6. Explore and implement cutting-edge technologies and tools in the data engineering space to improve efficiency and effectiveness.
7. Oversee the ETL (Extract, Transform, Load) processes, monitoring data flow, troubleshooting issues, and implementing optimizations as needed.
8. Collaborate with DevOps teams to manage and automate deployment pipelines, infrastructure provisioning, and monitoring systems.
9. Create and maintain documentation for data engineering processes, data lineage, data dictionaries, and best practices.
10. Stay updated with industry trends and advancements in data engineering and contribute to the continuous improvement of the data engineering practice within the organization.

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