Senior Data Engineer, Customer-Facing Data Products

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries.

It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for.

About The Role

The New York Times is looking for a Senior Data Engineer to join the Customer-Facing Data Products team to develop real-time data pipelines and APIs that process events and serve aggregated data for customer-facing use cases. You will report to the Engineering Manager for the Customer-Facing Data Products team and build widely reusable solutions to help partner teams solve our most important real-time needs, including behavioral and targeting use cases. This is a hybrid role based in our New York City headquarters.

Responsibilities

‬ Engineer and scale high availability data serving capabilities to meet customer-facing needs. ‬ Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world.

Qualifications

: 5+ years of full-time data engineering experience shipping real-time solutions with‬‭ event-driven architectures and stream-processing frameworks Experience with cloud native architectures (AWS preferred), including service offerings and tools Understanding of modern API design principles and technologies, including REST,‬‭ GraphQL, and gRPC for data serving Programming fluency with Python Experience using version control and CI/CD tools, such as Github Actions and Drone

Preferred Qualifications

: Experience developing streaming pipelines with Apache Kafka, Apache Flink, or Spark‬‭ Streaming Experience building APIs using Python frameworks (FastAPI, Flask) Experience with SQL Understanding of modern data platforms including data lakehouse‬‭ and medallion architectures Experience collaborating with product and partners to meet shared goals This role will require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

Base Pay Range

, dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock.

Benefits

may include medical, dental and vision

s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.

will be provided during the interview process. We’re excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process.