Data Engineer

A global nonprofit organization at the forefront of open knowledge is seeking a Data Engineer to help build the future of its data infrastructure. In this role, you'll contribute to unifying and scaling data systems that support analytics, machine learning, and operational insights across a complex and high-impact environment. You’ll work on a distributed team focused on enabling product innovation, research, and community engagement through clean, reliable, and governed data.

Benefits

• Competitive compensation based on experience, skills, and location.
• Fully remote role — work from anywhere in the world alongside a globally distributed team.
• Inclusive culture in a mission-driven organization supporting free access to knowledge.
• Comprehensive U.S. benefits, including health, dental, vision, 401(k), and paid leave (for U.S.-based employees).
• Opportunities for career growth, mentorship, and learning in open-source and large-scale systems.

Responsibilities

• Design and build scalable data pipelines using technologies such as Apache Airflow, Spark, and Kafka.
• Implement monitoring and alerting systems to proactively identify and resolve data quality issues.
• Contribute to data governance and lineage efforts, ensuring transparency and consistency across the data lifecycle.
• Collaborate with engineers, analysts, and stakeholders to evolve the shared data platform for use cases like analytics, automation, and machine learning.
• Enhance platform performance and reliability by identifying bottlenecks and optimizing systems.

Requirements

• 3+ years of professional experience in data engineering, including working with large-scale or on-premise systems (e.g., Hadoop, HDFS, Spark).
• Strong understanding of engineering best practices, with a focus on writing reliable and maintainable code.
• Proven ability to troubleshoot and optimize data systems for performance and scale.
• Preferred: Experience in system architecture or having taken technical ownership of a project or system.
• Preferred: Familiarity with data governance, lineage frameworks, and data quality assurance initiatives.