Senior Data Engineer(MainApp)

A Senior Data Engineer at Crypto.com is responsible for building a universal data platform that caters to both real-time and offline computing needs. They define data pipeline schemes based on varying demand scenarios and deliver them through multiple infrastructure methods. Additionally, they enhance the data platform, ensuring the stability and flexibility of data assets while optimizing resource efficiency.

To qualify for the Senior Data Engineer position at Crypto.com, candidates must hold a Bachelor’s degree or higher in computer science, big data, mathematics, or a related field, along with more than five years of data development experience. Familiarity with Hadoop, Spark, Flink, and Airflow is crucial, as well as an understanding of distributed system principles.

Essential skills for a Senior Data Engineer at Crypto.com include a strong grasp of data platform components like Hadoop, Spark, and Flink, along with optimization experience with these tools. In addition, good communication skills, logical thinking, self-drive, and a commitment to continuous learning are vital.

Crypto.com facilitates professional growth for Senior Data Engineers through various means, including a supportive work culture that values continuous learning, competitive salaries, and an internal mobility program that allows employees to explore diverse career paths.

Crypto.com provides a robust benefits package for its Senior Data Engineers, which includes competitive salaries, comprehensive medical insurance with extended coverage for dependents, attractive annual leave, flexible working hours, and perks such as a Crypto.com visa card upon joining.

When answering this question, focus on specific projects where you designed and implemented data pipelines. Discuss the tools you used, the challenges faced, and how you ensured the efficiency and reliability of those pipelines.

You should explain your methodology for identifying optimization opportunities. Discuss the performance metrics you monitor and share examples of improvements you've achieved using different data platform components.

When responding, explain the significance of distributed systems in data engineering, particularly in terms of scalability and reliability. Include any practical experiences you've had with distributed systems in your projects.

Discuss practices such as data validation processes, anomaly detection, and regular audits. Highlight tools or methodologies you've employed to maintain high data quality standards.

Select a project that showcases your technical skills and problem-solving abilities. Be ready to discuss the specific challenges, your approach to overcoming them, and the outcomes.

Share the resources and platforms you use, such as online courses, tech blogs, or community forums. Emphasize your proactive approach to learning and adapting to new technologies.

Discuss the tools you've used (like Spark, Flink, etc.), your preferences based on project requirements, and how these tools have benefitted your past projects.

Here, you should talk about specific big data projects you've worked on, the technologies you utilized, and how you tackled big data challenges.

Share examples of how you've effectively communicated with both technical and non-technical stakeholders to understand their needs and deliver data solutions accordingly.

Express your thoughts on balancing technical expertise with communication skills. Highlight the importance of understanding business needs and being able to translate those into data solutions.