Data Engineer I

1 World Trade Center, New York, NY

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Condé 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, Condé Nast Traveler/Traveller, Allure, AD, Bon Appétit and Wired, among others.

Job Description

Location:

New York, NY

Condé Nast is a premier media company renowned for producing the highest qualitycontent for the world's most influential audiences, attracting more than 100 million consumers across its industry-leading print, digital and video brands.
Condé 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 Condé Nast. Our mission is not only to inform readers but to ignite and nourish their passions.
The Data Solutions Engineering team have a wide range of responsibilities and play a critical role in shaping how Condé 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 subscriptions, video, clickstream, commerce, social and advertising within Condé 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:


● 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 relateddiscipline or relevant professional experience
● 2.5+ years of distributed data processing experience designing scalable &
automated software systems
● Experience in processing structured and unstructured data into a form suitable for analysis and reporting

● Experience with data modelling, batch data pipeline design and implementation
● Experience building batch or real-time data pipelines
● Proficiency in Python/PySpark or Scala
● Proficiency in SQL
● Experience with data processing frameworks such as Apache Spark (we use
Databricks)
● Experience in cloud-based infrastructures such as AWS or GCP
● Exposure to orchestration platforms such as Airflow (we use Astronomer)
● Proven attention to detail, critical thinking, and the ability to work independently
within a cross-functional team
● Comfortable with CI/CD (we use GitHub Actions) Pipelines
● Experience with Git version control, and other software adjacent tools
● Terraform is used Infra as service tool.

Salay Range: $119K - $137K

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.

Condé 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.

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Category: Engineering Jobs

Tags: Airflow AWS Business Intelligence CI/CD Computer Science Databricks Data pipelines Engineering GCP Git GitHub Machine Learning ML models Pipelines PySpark Python Scala Spark SQL Streaming Terraform Unstructured data

Region: North America
Country: United States

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