New York Times
Senior Data Engineer, Customer-Facing Data Products
New York Times, New York, New York, us, 10261
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
Develop real-time data pipelines using Apache Kafka, Apache Flink, and other streaming technologies. Ingest and organize structured and unstructured data for widespread reuse across patterns. Implement mechanisms to ensure data quality, observability and governance best practices. Collaborate with software engineers and infrastructure teams to improve pipeline performance and integrate solutions into production environments. Stay current with latest technologies, keeping up with the latest advancements in streaming data processing and related technologies. Grow the skills of colleagues by providing clear technical feedback through pairing, design, and code review. Experience collaborating with product and partners to meet shared goals. 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. Basic Qualifications:
5+ years of full-time data engineering experience shipping real-time solutions with event-driven architectures and stream-processing frameworks. Experience with AWS and their 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 and Drone. Preferred Qualifications:
Experience developing pipelines with Apache Kafka, Apache Flink, or Spark Streaming. Experience with SQL and building APIs with GoLang and Protobuf. Understanding of cloud-native data platform technologies including data lakehouse and medallion architectures. REQ-018499 The annual base pay range for this role is between: $140,000 - $155,000 USD
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
Develop real-time data pipelines using Apache Kafka, Apache Flink, and other streaming technologies. Ingest and organize structured and unstructured data for widespread reuse across patterns. Implement mechanisms to ensure data quality, observability and governance best practices. Collaborate with software engineers and infrastructure teams to improve pipeline performance and integrate solutions into production environments. Stay current with latest technologies, keeping up with the latest advancements in streaming data processing and related technologies. Grow the skills of colleagues by providing clear technical feedback through pairing, design, and code review. Experience collaborating with product and partners to meet shared goals. 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. Basic Qualifications:
5+ years of full-time data engineering experience shipping real-time solutions with event-driven architectures and stream-processing frameworks. Experience with AWS and their 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 and Drone. Preferred Qualifications:
Experience developing pipelines with Apache Kafka, Apache Flink, or Spark Streaming. Experience with SQL and building APIs with GoLang and Protobuf. Understanding of cloud-native data platform technologies including data lakehouse and medallion architectures. REQ-018499 The annual base pay range for this role is between: $140,000 - $155,000 USD