Principal Software Engineer, Data Platform at The New York Times

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

205000.0

Posted On

23 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Engineering, Distributed Systems, Data Platforms, Machine Learning Infrastructure, Data Processing Frameworks, Apache Spark, Apache Flink, Apache Iceberg, Cloud Platforms, AWS, GCP, Python, Java, Go, Kubernetes, Data Lakehouse, Compliance

Industry

Newspaper Publishing

Description

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 We are seeking a Principal Software Engineer to lead the architecture and evolution of our data and machine learning infrastructure. This role will shape the foundation on which data-driven products, analytics, and AI applications are built. You will design systems that enable large-scale data processing, reliable pipelines, and efficient machine learning development—from feature engineering to real-time model serving. As a principal engineer, you will partner with product, data science, and platform teams to set technical direction, drive adoption of reusable frameworks, and mentor engineers across the organization. You will ensure that both data and ML platforms are scalable, reliable, cost-efficient, and compliant with privacy and governance standards. The core of the Data Platform is a data lake on AWS S3 with Apache Iceberg as the table format to ensure reliability. Data ingestion is standardized through Confluent Kafka for real-time streaming and Fivetran for ingestion of files and change-data. The transformation layer is decoupled from storage, using Apache Flink for stream processing, AWS Glue (Spark) for core ETL , and dbt/Athena for building analytical data models. The platform serves data through fit-for-purpose data stores, including Amazon DynamoDB for low-latency applications and Google BigQuery as the primary engine for analytics and BI. This is a hybrid role based in our New York City headquarters, reporting to the Sr. Director of Engineering. You can typically expect to come into the office 2+ days per week. Responsibilities: Architect & Build Platform: Design and evolve infrastructure for data ingestion, storage, batch and streaming pipelines, and machine learning workflows. Enable ML at Scale: Build systems for training, deploying, monitoring, and governing models, including feature stores, registries, and inference platforms. Reliability & Observability: Ensure end-to-end system reliability, monitoring, and cost transparency across data and ML workloads. Self-Service Platforms: Deliver frameworks and APIs that enable engineers, analysts, and ML scientists to build and operate solutions independently. Innovation & Standards: Evaluate and introduce emerging technologies (vector databases, distributed training, orchestration frameworks, LLM stacks) and establish adoption guidelines. Cross-Functional Leadership: Partner with platform, product, and engineering and ML science leaders to align on strategy and accelerate delivery. Mentorship & Influence: Guide senior and staff engineers, lead architecture reviews, and raise the technical bar across data and ML domains. 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: 10+ years of software engineering experience with a focus on distributed systems, data platforms, and ML infrastructure or equivalent Proven ability to influence technical direction across multiple teams and mentor senior/staff engineers Proven expertise in data processing frameworks and table formats (e.g. Spark, Flink, Iceberg) and orchestration tools (e.g. Airflow, Kubeflow) Deep knowledge of ML infrastructure: model training pipelines, feature stores, registries, serving, and monitoring Strong programming skills in Python and at least one compiled language like Java or Go Experience designing systems with scalability, reliability, and cost-efficiency as first-class concerns Cloud platform experience (AWS, GCP), familiarity with Kubernetes and modern data platform architectures Preferred Qualifications: Familiarity with compliance and governance in data/ML systems (auditability, privacy, explainability) Familiarity with the data lakehouse paradigm and medallion architecture #LI-Hybrid REQ-018968 The annual base pay range for this role is between: $198,000—$205,000 USD The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply. We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here. The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email reasonable.accommodations@nytimes.com. Emails sent for unrelated issues, such as following up on an application, will not receive a response. The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For information about The New York Times' privacy practices for job applicants click here. Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site. The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times. If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at NYTapplicants@nytimes.com. You can also file a report with the Federal Trade Commission or your state attorney general.

Responsibilities

Lead the architecture and evolution of data and machine learning infrastructure. Design systems for large-scale data processing, reliable pipelines, and efficient machine learning development.