Our team is expanding due to significant growth in new projects and data volume. We are seeking motivated and skilled Data Engineers to join our dynamic data warehousing team. This is not a backfill; you will be joining a growing function responsible for building and scaling the data infrastructure that powers our internal operations.

You will play a crucial role in developing and maintaining robust ETL pipelines using a modern tech stack centered on Google Cloud Platform (GCP) and Python. While our ideal candidate has GCP experience, we are committed to investing in the right talent and are open to cross-training individuals with strong foundational database and Python skills from other cloud (AWS/Azure) or on-premise environments.

This is a hands-on development role where you will take ownership of your work from design through to a post-deployment warranty period, ensuring the quality and reliability of our data flows.

Key Responsibilities:

• Design, develop, and maintain scalable and efficient ETL pipelines to extract data from various sources, transform it, and load it into Google BigQuery.

• Write high-quality, maintainable Python code for data processing and transformation, leveraging core libraries such as Pandas and NumPy.

• Author and troubleshoot complex SQL queries to support data extraction, transformation, and analysis within our data warehouse.

• Collaborate with team members and stakeholders in an Agile/Scrum environment to deliver features in sprints.

• Provide post-deployment support for your developed solutions for a 3-month "warranty period," which includes monitoring jobs, identifying issues, and deploying fixes.

• Engage with teams in different time zones (primarily Central America) for requirements clarification and issue resolution, requiring some flexibility in work hours.

• Contribute to the overall architecture and design of our data solutions, ensuring they are robust and performant.