Data Engineer III
Condé Nast India · Greater Chennai Area
- On site
- Full-time
- ₹1,500,000 / year
- Greater Chennai Area
Job highlights
- Build and maintain reliable data pipelines.
- Empower data scientists and analysts.
- Work with AWS, Python, SQL, Spark.
- Collaborate on a shared technical vision.
- Mentor junior engineers and review code.
About the role
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
Skills & topics
- Data Engineer
- Data Pipelines
- AWS
- Python
- SQL
- Spark
- Databricks
- Data Modeling
- ETL
- Cloud Computing
- Big Data
- Software Development
- Streaming Data
- Batch Processing
- Business Intelligence
- Data Architecture
- Agile
- CI/CD
- IaC
- Mentorship
How to get hired
- Tailor your resume: Highlight experience with data pipelines, AWS services (Kinesis, DynamoDB, S3), Python/PySpark, SQL, and Databricks/Spark. Quantify achievements where possible.
- Showcase your skills: Emphasize your experience in building scalable, distributed systems and your ability to process structured and unstructured data.
- Demonstrate leadership potential: Include examples of mentoring junior engineers, performing code reviews, and contributing to architectural designs.
- Prepare for technical questions: Be ready to discuss data modeling, batch data pipeline design, CI/CD, and IaC tools like Terraform.
- Understand Condé Nast's data ecosystem: Research their business areas (subscriptions, video, commerce, etc.) and how data engineering supports them.
Technical preparation
Master Python/PySpark, Scala, Java, and SQL.,Practice AWS services: Kinesis, DynamoDB, S3.,Build data models and ETL pipelines.,Familiarize with Airflow, Databricks, Terraform.
Behavioral questions
Describe a challenging data pipeline project.,How do you mentor junior engineers?,Explain a complex data concept simply.,How do you ensure data quality and accuracy?
Frequently asked questions
- What are the key technologies used by the Data Engineer III role at Condé Nast?
- The Data Engineer III role at Condé Nast heavily utilizes AWS services like Kinesis, DynamoDB, and S3. Proficiency in Python/PySpark, Scala, or Java, along with SQL, is essential. Experience with Databricks/Spark, orchestration tools like Airflow, CI/CD pipelines (GitHub Actions), and Infrastructure as Code (Terraform) are also critical.
- What kind of data sources will a Data Engineer III work with at Condé Nast?
- A Data Engineer III at Condé Nast will work with a diverse range of data sources, including batch data and real-time streams. These sources span various business areas such as subscriptions, video, clickstream, commerce, social media, and advertising, enabling comprehensive data analysis and reporting.
- Does Condé Nast offer opportunities for mentorship and leadership for a Data Engineer III?
- Yes, the Data Engineer III role specifically mentions experience in mentoring and supporting junior team members. You will also serve as a senior technical contact and perform code reviews, indicating opportunities to guide and lead technical initiatives within the team.
- What is the required educational background for the Data Engineer III position at Condé Nast?
- Condé Nast requires a BS, MS, Ph.D., or equivalent industry experience in Computer Science, Software Engineering, or a related STEM field for the Data Engineer III position. The emphasis is on practical experience and knowledge rather than a specific degree alone.
- How does the Data Engineer III role contribute to Condé Nast's business objectives?
- The Data Engineer III plays a crucial role by building and maintaining data pipelines and products that enable Data Scientists, Analysts, and Executives. This facilitates solving challenging business use cases across subscriptions, video, commerce, social, and advertising, directly impacting business decisions and strategy.
- What is the expected level of autonomy for a Data Engineer III at Condé Nast?
- The job description highlights the expectation of working on independent projects with very minimal supervision. This suggests a high degree of autonomy is expected, where the Data Engineer III can take ownership of tasks and drive them to completion effectively.
- How important is communication for the Data Engineer III role at Condé Nast?
- Exceptional communication skills are highly valued. The role requires effectively communicating and visualizing quantitative findings in a compelling and actionable manner for business stakeholders, bridging the gap between technical data and business strategy.