Senior Data Engineer

As a Senior Data Engineer at Magic Eden, your primary responsibilities will include serving as a technical expert, collaborating with teams to identify data needs, designing and building the next generation of data infrastructure, and creating reliable data pipelines using modern processing technologies. Additionally, you'll foster team growth by mentoring junior members and promoting best practices in data architecture, coding standards, and big data platforms.

To qualify for the Senior Data Engineer position at Magic Eden, you should have at least a Bachelor's or Master's degree in Computer Science or a related field. You’ll also need 10+ years of experience in big data, a strong understanding of data modeling, extensive experience with distributed processing technologies like Spark and Hive, and proficiency in SQL and NoSQL databases. Familiarity with cloud computing platforms such as AWS is highly desirable.

At Magic Eden, professional development is a priority. Senior Data Engineers are encouraged to mentor others, foster best practices, and engage in ongoing learning opportunities. The fast-paced and collaborative environment ensures that you’ll be working alongside talented individuals, which naturally supports knowledge sharing and skill enhancement. Additional resources for personal and professional development are also available.

For the Senior Data Engineer position at Magic Eden, you'll need a strong background in distributed processing technologies such as Spark, Kafka, and data warehousing solutions like Redshift and Presto. Familiarity with building data pipelines, extensive knowledge of SQL and NoSQL databases, and some experience in programming languages such as Python or Scala will also be crucial for your success in this role.

Magic Eden offers a fast-paced, collaborative work culture where innovation thrives. As a Senior Data Engineer, you'll work in a supportive environment that encourages flexibility with options like remote work, wellness allowances, and flexible PTO. The team consists of passionate and talented individuals who are committed to reshaping the onchain experience and making a meaningful impact in the crypto space.

In response to this question, it’s essential to highlight specific experiences you've had with technologies like Spark, Kafka, and any big data platforms you've worked on. Discuss projects where you implemented data pipelines and how your expertise led to performance improvements or more efficient data processing.

When answering this question, emphasize the importance of understanding data sources, data volume, and the required processing speed. Discuss frameworks you prefer and any methodologies you follow to ensure data quality and reliability throughout the pipeline.

Be ready to discuss the programming languages you’ve used frequently. Examples such as Python, Scala, or R are beneficial, so detail projects where you've utilized these languages for data manipulation or pipeline creation.

Provide insights into your background involving data modeling techniques and concepts. Discuss your familiarity with various data warehousing solutions and how you’ve implemented these concepts in past projects to meet business needs.

In your answer, discuss specific methods you use to validate data, such as data quality checks or monitoring systems. Share examples of how you’ve corrected data issues and prevented them from recurring.

Discuss how your communication skills have helped you work effectively with teams beyond data engineering, such as product managers, business analysts, and developers. Provide examples of successful projects that utilized cross-departmental collaboration.

Explain which metrics you track, such as latency, throughput, and error rates, and emphasize the critical nature of these metrics in optimizing performance. Provide insights into how you've utilized such metrics in past roles to drive improvements.

Detail your experience with cloud services like AWS, Azure, or Google Cloud. Discuss your role in a project, the services used, and how you addressed scalability and reliability concerns while implementing solutions.

Share the resources you use for keeping up with trends, such as blogs, forums, online courses, or professional communities. Discuss how you’ve taken this knowledge and applied it to improve your work or contribute to your team's success.

Provide specific examples of challenges in your previous roles and detail the steps you took to address these issues. Highlight any innovative solutions you implemented and the impact they had on your projects.