Senior data engineer

Who we areAt Frontiers, our purpose is simple yet ambitious: to make science open. We believe open science empowers the global scientific community to accelerate discovery and develop the solutions needed for healthy lives on a healthy planet. We are one of the world’s largest and most influential open-access research publishers. Every article we publish is peer-reviewed and quality-certified, ensuring research is accessible to everyone, everywhere. To date, Frontiers research has been viewed over 4 billion times, demonstrating the real-world impact of science without barriers. Joining Frontiers means being part of a global, mission-driven organization at the intersection of science, technology, and innovation — working alongside passionate colleagues who care deeply about advancing knowledge for the benefit of society. To learn more about our impact and culture, please watch this video: https://www.youtube.com/watch?v=jLJ7ZO3wOW4

About the Role:  • Own and evolve the company’s data infrastructure: event tracking, ingestion pipelines, and analytics tooling • Manage data collection pipelines via Snowplow, GTM (server-side and client-side), and Airflow-orchestrated workflows running on Cloud Composer • Build and maintain BigQuery datasets: partitioning, clustering, cost optimization, scheduled queries, and access controls • Write and maintain Python scripts for data ingestion, transformation, and reporting • Manage Cloud Storage (GCS) for data staging, Snowplow enriched event storage, and pipeline artifacts • Configure and maintain GCP IAM, service accounts, and access controls across services and external APIs • Monitor and debug pipelines using Cloud Logging & Monitoring; set up alerting and ensure pipeline observability • Work with relational and non-relational databases: schema design, query optimization, performance tuning • Collaborate with frontend, QA, DevOps, and product teams • Participate in code reviews and uphold code quality standards • Contribute to technical improvements (testing, observability, performance, maintainability) • Mentor mid-level engineers and contribute to architectural decisions