Data Engineer III

About the Role

The Global Data Engineering team at Condé Nast has broad responsibilities and plays a critical role in leveraging data to drive business decisions. This team is responsible for building data pipelines, data products, and tools that empower Data Scientists, Analysts, Business Intelligence Engineers, and Executives to tackle complex industry challenges. We are looking for a Data Engineer to build and maintain data pipelines across various business areas including subscriptions, video, clickstream, commerce, social, and advertising within Condé Nast. If you thrive in a challenging environment and wish to collaborate with a world-class data engineering team at a well-established company, we encourage you to join us.

Responsibilities

Responsibilities include, but are not limited to:

• Build, test, scale, and maintain highly reliable data pipelines from a variety of batch data sources and real-time streams.
• Contribute to the data infrastructure and platform used for building data pipelines.
• Serve as a core member of the data engineering team, proficient in assisting the business with understanding data attributes.
• Design and present recommendations to guide future business and research directions.
• Build and maintain highly validated data marts with ensured clarity and correctness of key business metrics for BI reporting purposes.
• Collaborate with other Data Engineers, Data Scientists, and BI Engineers to architect and implement a shared technical vision.
• Follow agile processes with a focus on delivering production-ready, testable deliverables iteratively.
• Serve as a senior technical contact for the data solutions engineering team.
• Perform code reviews and in-depth technical reviews of system design architectures for junior engineers.
• Participate in the entire software development lifecycle, from concept to release.

Minimum Qualifications

• BS, MS, Ph.D., or equivalent industry experience in Computer Science, Software Engineering, or other related fields (Science/Technology/Engineering/Math).
• 3+ years of experience in near-real-time (Streaming) & Batch Data Pipeline development in a large-scale organization.
• 7.5+ years of relevant experience in software development in total.
• Experience in writing reusable and efficient code to automate analysis and data processes.
• 2+ years of business/marketing analytics experience, preferably in a consumer-based organization.
• Experience successfully working on an independent project with minimal supervision.
• Experience processing structured and unstructured data into a form suitable for analysis and reporting, integrating with various data metric providers (web analytics, consumer analytics, advertising).
• Strong experience with data modeling, batch data pipeline design, and implementation.
• Strong experience in software development and engineering principles.
• Experience implementing scalable, distributed, and highly available systems using AWS services such as Kinesis, DynamoDB, and S3.
• Exceptional communication skills, particularly in communicating and visualizing quantitative findings compellingly and actionably for business stakeholders.
• Experience mentoring and supporting junior team members.
• High proficiency in Python/PySpark, Scala, or Java.
• High proficiency in SQL.
• Experience with Databricks/Spark.
• Experience with orchestration tools such as Airflow.
• Comfortable with CI/CD (GitHub Actions) Pipelines.
• Experience with Git version control and other software adjacent tools.
• Experience with Terraform or other Infrastructure as Code (IaC) tools.

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.

Equal Opportunity Employer

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.

Key skills/competency

• Data Engineering
• Data Pipelines
• AWS
• Python
• SQL
• Spark
• Databricks
• Data Modeling
• ETL
• Cloud Computing