About the RoleThe 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-$155,000 USD
For roles in the U.S., 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 benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs.
For roles outside of the U.S., information on benefits will be provided during the interview process.
