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 event-driven architectures and streaming technologies.
- Ingest and organize structured and unstructured data for widespread reuse across patterns.
- Engineer and scale high availability data serving capabilities to meet customer-facing needs.
- 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.
- Grow the skills of colleagues by providing clear technical feedback through pairing, design, and code review.
- Stay current with latest technologies, keeping up with the latest advancements in streaming data processing and related technologies.
- 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 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.
#LI-Hybrid
REQ-020049
The annual base pay range for this role is between:
$140,000 - $160,000 USD
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