As a Data Engineer, your day-to-day involves architecting, building, and maintaining robust data solutions critical for data generation, collection, and processing. You will be responsible for developing efficient data pipelines, ensuring high data quality, and implementing ETL processes for seamless data migration and deployment across various systems.

This role demands continuous collaboration with diverse teams to optimize data management and effectively support the organization's data objectives. The position requires a deep understanding of data integration techniques and ETL processes, along with experience in cloud-based data storage and processing environments. You'll work with both structured and unstructured data to maintain data integrity and consistency.

Independently perform duties and establish yourself as a Subject Matter Expert (SME). Actively contribute to and participate in team discussions and problem-solving sessions. Deliver scalable data solutions by collaborating with cross-functional teams to understand and meet data requirements. Monitor and troubleshoot data pipelines diligently to ensure optimal reliability and performance. Maintain clarity and facilitate knowledge sharing by documenting data processes and workflows. Provide guidance and support to junior team members, sharing insights into data engineering concepts and best practices.

Demonstrated proficiency in Snowflake Data Warehouse is essential. Experience in designing and optimizing data pipelines for large-scale data processing is required. Strong understanding of data integration techniques and ETL processes is necessary. Familiarity with cloud-based data storage and processing environments is beneficial. Ability to effectively manage structured and unstructured data to ensure data quality and consistency. A minimum of 3 years of experience in Snowflake Data Warehouse is mandatory. A foundation of 15 years of full-time education is a prerequisite for this role.