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Advance Magazine Publishers Inc. Data Engineer I in New York, New York

Conde Nast is a global media company producing the highest quality content with a footprint of more than 1 billion consumers in 32 territories through print, digital, video and social platforms. The company's portfolio includes many of the world's most respected and influential media properties including Vogue, Vanity Fair, Glamour, Self, GQ, The New Yorker, Conde Nast Traveler/Traveller, Allure, AD, Bon Appetit and Wired, among others. Conde Nast Entertainment was launched in 2011 to develop film, television and premium digital video programming.
Job Description
Conde Nast is a premier media company renowned for producing the highest quality content for the world's most influential audiences, attracting more than 100 million consumers across its industry-leading print, digital and video brands.

Conde Nast is home to many of the world's most-celebrated magazine and website brands. The company's reputation for excellence is the result of our commitment to publishing the best consumer, trade, and lifestyle content. Our brands include Vogue, Epicurious, Vanity Fair, The New Yorker, Wired, and many more. Passion is the core of our philosophy at Conde Nast. Our mission is not only to inform readers but to ignite and nourish their passions.
The Data Engineering team within the Data Organization have a wide range of responsibilities and play a critical role in shaping how Conde Nast enables its business using data. The team is responsible for building data pipelines, data products and tools that enable our Data Scientists, Analysts in various business units, Business Intelligence Engineers and Executives to solve challenging use cases in our industry.

We are seeking a Data Engineer who will build and maintain data pipelines across business areas such as consumer revenue, video, clickstream, commerce, social and ad revenue within Conde Nast. If you are looking for a challenging environment and to work with a world class team of data engineers in a well balanced environment and seasoned company, come join us:

RESPONSIBILITIES
Responsibilities include, but are not limited to:

Design, build and test batch and streaming data pipelines capable of processing large volumes of data

Build efficient code to transform raw data into datasets for analysis, reporting and machine learning models

Collaborate with other data engineers to implement a shared technical vision

Participate in the entire software development lifecycle, from concept to release

MINIMUM QUALIFICATIONS

Applicants should have a degree (B.S. or higher) in Computer Science or a related discipline or relevant professional experience

1+ years of software development experience designing scalable & automated software systems

Experience in processing structured and unstructured data into a form suitable for analysis and reporting

Experience building batch or real-time data pipelines

Proficiency in Python/PySpark or Scala

Proficiency in SQL

Experience with data processing frameworks such as Spark, Flink, or Beam

Experience in cloud-based infrastructures such as AWS or GCP

Exposure to orchestration platforms such as Airflow or Kubeflow

Proven attention to detail, critical thinking, and the ability to work independently within a cross-functional team
What happens next?
If you are interested in this opportunity, please apply below, and we will review your application as soon as possible. You can update your resume or upload a cover letter at any time by accessing your candidate profile.

Conde Nast is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, age, familial status and other legally protected characteristics.

Conde Nast is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.

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