Location:
Chennai, TNAbout Role: The Global Data 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
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 to build our data pipelines
Serve as a core member of the data engineering team and be 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 in an iterative fashion
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 Science/Technology/Engineering/Math fields.
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/efficient code to automate analysis and data processes
2+ years of business/marketing analytics experience, preferably in a consumer-based organisation
Experience successfully working on an independent project with very minimal supervision
Experience in processing structured and unstructured data into a form suitable for analysis and reporting, with integration with a variety of data metric providers, ranging from web analytics, consumer analytics, and advertising
Strong Experience with data modelling, 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 in a compelling and actionable manner for business stakeholders
Experience in mentoring and supporting junior members of the team
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 (we use GitHub Actions) Pipelines
Experience with Git version control and other software adjacent tools
Experience with Terraform or other Infrastructure as Code (IaC) tools.
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.
