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. 

Qualifications: 

Experience building and supporting data pipelines and warehousing solutions ? Experience working with SQL and a solid understanding of Data Modeling

Strong software development experience utilizing a programming language such as Python or Java 

Experience with data transformation utilizing frameworks such as dbt 

Experience with distributed systems and event-driven architectures 

Knowledge of different databases and storage technologies, like relational DBMSs, columnar storage, and key-value stores. 

Experience with data extraction and load tools such as FiveTran 

Experience developing, maintaining, and monitoring an enterprise-wide data platform

Experience in Unix environment and shell scripting 

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

Experience working with cloud platforms like GCP or AWS

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