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 newsroom that’s 1,700 strong and 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. 

Note for US based roles: Any offer of employment is contingent on providing proof of Covid-19 vaccination prior to your start date, subject to approved medical and/or religious exemptions, in accordance with applicable law.

Job Description

The New York Times is seeking inventive and motivated data engineers at all levels of experience to join the Data Engineering group. In this role, you will build critical data products that surface data and insights across the company.

About Us

Our Data Engineering teams are at the intersection of business analytics, data warehousing, and software engineering. As Maxime Beauchemin wrote in “The Rise of Data Engineering”, ETL and data modeling have evolved, and the changes are about distributed systems, stream processing, and computation at scale. They’re about working with data using the same practices that guide software engineering at large.

A strong data foundation is essential for The New York Times and we’re responsible for it. We use our data infrastructure to power analytics and data products and to deliver relevant experiences to our customers in real-time. We enable our company to validate strategic decisions, make smarter choices, and react to the fast changing world. 

We are part of a New York based technology organization with a remote-friendly workplace that includes engineers around the world. We value transparency and openness, learning, community, and continuous improvement. Check out the Times Open blog, which is written by engineers and other technical team members, and follow @nytdevs on Twitter to see what we’re up to.

About the Job

At Subscriber Data Products (SDP), we focus on the software engineering related to the consuming and processing of subscription domain events in order to clean, store and transform subscription and revenue data into timely, trustworthy, accessible and meaningful analytics schemas for the business to use to understand key metrics of our core digital and home-delivery subscription business.

We reduce data redundancy by creating systems and datasets that serve as domain data products. We enable discovery and governance of our data. We support key business goals like growing our digital subscriber base, understanding how our customers use our products, and retaining our print subscribers.

As a data engineer, you will:

• Modernize and simplify subscriber data pipelines and datasets by utilizing SQL modeling in dbt

• Work closely with business partners and analysts to design and implement data models and audits of mission-critical metrics to ensure data-correctness and freshness SLOs are met.

• Automate tasks such as end-to-end testing and report generation

• Build transformation pipelines with tools such as BigQuery, dbt, Airflow, FiveTran, Mode and other services in Google Cloud Platform using languages such as Python, Go & SQL

About You

To thrive in this role, you are excited about data and motivated to learn new technologies. You are comfortable collaborating with engineers from other teams, product owners, business teams, and data analysts and data scientists. You own and shape your technical domain area and move the related business goals forward. You are eager to resolve upstream data issues at the source instead of applying workarounds. You analyze and test changes to our data architectures and processes, and determine what the possible downstream effects and potential impacts to data consumers will be.

Minimum Qualifications:

• Bachelor’s degree or equivalent practical experience

• Experience working with SQL

• 2 years experience with backend systems and software engineering. Programming experience in a relevant language, e.g. Python, Java

• 2 years experience working with cloud platforms like GCP or AWS

Preferred Qualifications:

• Experience with distributed systems, databases, data modeling and data transformation (dbt, Spark)

• Experience building and supporting data pipelines and warehousing solutions

• Experience with data extraction and load tools such as FiveTran

• Experience with automation, testing, build tools, and release engineering

This role may require limited on-call hours. An on-call schedule will be determined when you join, taking into account team size and other variables.

#LI-AM1

The New York Times is committed to a diverse and inclusive workforce, one that reflects the varied global community we serve. Our journalism and the products we build in the service of that journalism greatly benefit from a range of perspectives, which can only come from diversity of all types, across our ranks, at all levels of the organization. Achieving true diversity and inclusion is the right thing to do. It is also the smart thing for our business. So we strongly encourage women, veterans, people with disabilities, people of color and gender nonconforming candidates to apply.

The New York Times Company is an Equal Opportunity Employer and does 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 New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws, and will consider qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable "Fair Chance" laws.