Senior Data Engineer, Data Infrastructure

As a Senior Data Engineer at Zocdoc, your main responsibilities include designing and maintaining scalable data pipelines, collaborating with product teams to curate valuable datasets, developing modern data architectures, and optimizing performance on platforms like Snowflake. You will also support orchestration platforms and collaborate with cross-functional teams to ensure efficient data workflows.

To qualify for the Senior Data Engineer position at Zocdoc, you should have at least 5 years of experience in data engineering, with expertise in Python or Scala, and strong SQL skills. A solid background in data warehousing technologies like Snowflake and experience with data lake architectures is crucial. Familiarity with infrastructure management and a proactive problem-solving approach are also essential.

Zocdoc is dedicated to the development of its team members. As a Senior Data Engineer, you’ll benefit from a collaborative environment that encourages continuous learning and experimentation. You'll have the opportunity to work with cutting-edge technologies and tackle complex problems while also having access to wellness programs and a supportive workplace.

In the role of Senior Data Engineer at Zocdoc, you will utilize a variety of modern tools and technologies such as Databricks, Snowflake, Dagster for orchestration, and Datadog for monitoring. You’ll work on developing scalable ETL pipelines and optimize database performance, ensuring robust data infrastructure for analytics and machine learning.

Zocdoc fosters a highly collaborative and inclusive culture, emphasizing teamwork among its Senior Data Engineers and other departments. With a mission-driven mindset, the company values diverse perspectives and aims to create a work environment that is fair and equitable. Regular team interactions, opportunities for professional development, and a supportive atmosphere are hallmarks of the Zocdoc culture.

In your response, focus on specific projects where you designed data pipelines. Highlight the technologies you used, the challenges you faced, and how your designs improved data flow. Be sure to mention any metrics or results that demonstrate the impact of your work.

Discuss your processes for validating data, including testing strategies and monitoring systems. Mention any tools you have utilized for data quality management, and how you tackle issues when they arise in the pipeline.

Outline your familiarity with Snowflake's features, including performance tuning, clustering, and query optimization. Share experiences where you've successfully implemented these strategies to achieve better performance with real-world examples.

Talk about your strategies for scaling, such as sharding or implementing more efficient data models. Provide examples of past projects where you successfully scaled data architectures while ensuring minimal disruption and costs.

Use the STAR method to describe the problem-situation-task-action-result. Be clear about the technical aspects you involved yourself in, the methodologies you applied, and how the solution benefited the project or organization.

Discuss data source reliability, transformation logic, and performance aspects, like minimizing latency. Be prepared to share your experience using tools like dbt or similar ETL frameworks.

Explain how you engage in continuous learning. This may include participating in online courses, attending industry conferences, following key thought leaders on social media, or contributing to open-source projects.

Share examples of projects where you worked with analytics teams, product managers, and stakeholders. Highlight your communication strategies and how you ensured alignment throughout the project's lifecycle.

Emphasize your experience implementing data governance tools and processes, focusing on specific outcomes. Discuss how you established protocols that governed access, usage, and quality of data.

Talk about your understanding of data privacy regulations (like GDPR or HIPAA), and your approach to ensuring data is protected through encryption, access controls, and audits. Be ready to give examples of security measures you’ve implemented.