Overview
This article features an interview with Dhevi Rajendran, a Data Engineer at Netflix, discussing her journey into data engineering, her role in the Growth Data Science and Engineering team, and her experiences onboarding during the pandemic. Dhevi shares insights about the culture at Netflix, the importance of data engineering, and her favorite projects.
What You'll Learn
1
How to effectively collaborate in cross-functional teams as a data engineer
2
Why understanding user payment preferences is crucial for global services
3
How to adapt to new technologies in a remote onboarding environment
Prerequisites & Requirements
- Background in software engineering or data engineering
Key Questions Answered
What motivated Dhevi Rajendran to pursue a career in data engineering?
Dhevi Rajendran was motivated by her background in backend software engineering and the impactful nature of data engineering. She enjoys the technical challenges and the ability to solve real-world problems using data, which she finds rewarding.
How does Netflix's culture influence its engineering practices?
Netflix's culture emphasizes freedom and responsibility, allowing engineers to make decisions based on their knowledge and context. This approach reduces red tape and fosters a collaborative environment where input into strategic decisions is valued.
What challenges did Dhevi face while onboarding during the pandemic?
Dhevi faced challenges in building relationships and gathering context while onboarding remotely. She learned to be proactive in seeking out opportunities to connect with colleagues and understand the business better, which helped her adapt to the new role.
What is Dhevi's favorite project at Netflix?
Dhevi enjoys participating in cross-functional meetings related to the payments space, where she collaborates with diverse teams including product managers and data scientists. This involvement allows her to contribute to high-level discussions and understand payment preferences across different countries.
Technologies & Tools
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Backend
Scala
Used in the technologies Dhevi's team employs for data engineering tasks.
Backend
Spark
Another technology utilized by Dhevi's team for processing large datasets.
Key Actionable Insights
1Engage in cross-functional meetings to enhance your understanding of diverse perspectives in data engineering.Working with various roles such as product managers and designers can provide valuable insights and improve the quality of your data solutions.
2Embrace remote onboarding by proactively seeking connections and learning opportunities.Building relationships and understanding the company culture are crucial, especially in a remote setting. Taking initiative can lead to a smoother transition into your new role.
3Familiarize yourself with the specific payment preferences of users in different regions.Understanding these preferences can significantly impact how you design data products and improve user experience on a global scale.
Common Pitfalls
1
Failing to proactively build relationships during remote onboarding can lead to feelings of isolation and hinder learning.
Without in-person interactions, it's easy to miss out on valuable insights and support from colleagues. Actively reaching out can mitigate this issue.