As a Data Engineer, your day-to-day will focus on designing, developing, and maintaining robust data solutions. This involves creating efficient data pipelines for generation, collection, and processing, while ensuring data quality. You'll implement ETL processes for seamless data migration and deployment across systems, collaborating with teams to optimize data handling and meet organizational needs.

This role is crucial for enabling the responsible use of AI and data science to transform business operations. It offers the opportunity to uncover new possibilities and reinvent all facets of business.

Take ownership of your work, becoming a subject matter expert and actively contributing to team discussions. Provide solutions to work-related challenges and collaborate with cross-functional teams to deliver scalable data solutions aligned with requirements.

Monitor and troubleshoot data pipelines for optimal reliability and performance. Document data processes and workflows for clarity and knowledge sharing. Support junior team members by sharing insights on data engineering concepts and best practices.

A minimum of 3 years of experience in Snowflake Data Warehouse is essential. Strong proficiency in designing and optimizing data pipelines for large-scale data processing is required. You should possess a solid understanding of data integration techniques and ETL processes.

Familiarity with cloud-based data storage and processing environments is beneficial. The ability to work with both structured and unstructured data to maintain data quality and consistency is key. A complete 15 years of full-time education is a mandatory requirement for this role.