Principal Data Engineer

As a Principal Data Engineer at Covera Health, your primary responsibilities include designing and maintaining the data infrastructure that powers our healthcare solutions. You'll build and manage data pipelines, ensure data integrity, and enable near real-time data processing for decision-making. You will also collaborate with various teams to create data models and schemas that support new business initiatives.

Candidates for the Principal Data Engineer role at Covera Health should have at least 7 years of data engineering experience. Proficiency in Python, experience with large-scale data architectures, and familiarity with cloud technologies like Databricks and Azure are essential. Strong communication skills for collaboration across teams are also important.

The Principal Data Engineer plays a critical role in Covera Health's mission to improve healthcare quality. By designing effective data pipelines and ensuring seamless data flow, you contribute to better decision-making and enhanced patient outcomes, ultimately impacting the quality of care received by millions.

In the Principal Data Engineer role at Covera Health, you will utilize modern data stack tools and cloud technologies such as Databricks, Spark, and Postgres. Experience with structured and unstructured data modeling and performance tuning will also be key components of your work.

Yes, Covera Health is a remote-first company, although there is an option to collaborate in our NYC office. Many employees choose to come in for team-building days. We value flexibility while also fostering connections among our team members.

When answering this question, focus on specific projects where you constructed data pipelines. Discuss the technologies you used, the challenges you faced, and how you ensured data quality and integrity throughout the process.

Explain your systematic approach to data normalization, perhaps discussing how you assess data quality and make decisions on alignment with internal standards. Highlight any tools or methodologies you frequently employ.

Share an example where you successfully implemented near real-time data processing. Detail the technologies involved and how you managed data latency challenges while ensuring that data remained reliable.

Be prepared to share a specific challenge related to data volume or complexity. Explain how you tackled the situation, what solutions you implemented, and any lessons learned that improved your future work.

Discuss your preferred data modeling techniques, such as star schema or snowflake schema, and explain their applications in various scenarios. Use examples to illustrate effective implementation in prior roles.

Share your communication strategies and tools that promote collaboration. Highlight your belief in the importance of clear documentation and regular syncs between teams to ensure everyone is aligned on data usage and requirements.

Discuss your experience with cloud technologies like Azure or AWS, emphasizing how you leveraged them in previous projects to enhance scalability and performance of data solutions.

Explain the methods you utilize for performance tuning, such as optimizing queries, indexing, or partitioning. Provide examples of situations where your tuning led to measurable improvements in system performance.

Illustrate how you keep pace with the evolving data engineering landscape by following industry publications, participating in relevant communities, and investing time in professional development through courses or certifications.

Convey your enthusiasm for Covera Health's mission and the opportunity to leverage your skills to make a tangible impact in healthcare. Discuss what specifically draws you to the company culture and its commitment to quality.