Data Engineer, Customer-Facing Data Products

The New York Times, a leading global news organization, is seeking a Data Engineer to join their Customer-Facing Data Products team. This role focuses on developing real-time data pipelines and APIs that process events and serve aggregated data for customer-facing use cases. The position offers an opportunity to work with cutting-edge streaming technologies like Apache Kafka and Flink while building solutions that directly impact the company's real-time behavioral and targeting capabilities.

The role is based in their New York City headquarters with a hybrid work arrangement, offering a balance between in-office collaboration and remote work flexibility. The position comes with a competitive salary range of $110,000 to $130,000 USD annually, reflecting the technical expertise required and the impact of the role.

As a Data Engineer, you'll be at the intersection of data infrastructure and customer experience, developing widely reusable solutions that help partner teams address critical real-time needs. You'll work with modern technologies including AWS, various streaming frameworks, and multiple programming languages, particularly Python and Go. The role requires both technical expertise in data engineering and the ability to collaborate effectively with cross-functional teams.

The New York Times offers a unique opportunity to work for an organization with a strong mission of seeking truth and helping people understand the world. You'll be part of a company that values journalistic independence and invests heavily in both traditional and digital journalism. The role combines technical challenges with the satisfaction of contributing to one of the world's most respected news organizations.

The ideal candidate will bring at least 2 years of data engineering experience, strong programming skills, and familiarity with modern API design principles. The position offers growth opportunities through mentoring colleagues and staying current with the latest technological advancements in data processing.