Staff Data Engineer
Imagine Pediatrics
Description
Who We Are
Imagine Pediatrics is a tech enabled, pediatrician led medical group reimagining care for children with special health care needs. We deliver 24/7 virtual first and in home medical, behavioral, and social care, working alongside families, providers, and health plans to break down barriers to quality care. We do not replace existing care teams; we enhance them, providing an extra layer of support with compassion, creativity, and an unwavering commitment to children with medical complexity.
What You'll Do
As a Staff Data Engineer at Imagine Pediatrics, you will be the first dedicated Data Engineer on a hybrid team with Analytics Engineers, responsible for defining how data moves through our platform and owning the data pipelines that power clinical analytics, operational reporting, and external integrations.
You will ensure that data ingestion and integration decisions are made with a clear understanding of downstream analytical usage, including how data freshness, grain, and structure impact downstream processes and systems. You will partner closely with Analytics
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About Imagine Pediatrics
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Interview Prep Guide
Preparation Strategy
To prepare for this role, focus on reviewing data engineering concepts, practicing system design interviews, and developing your ability to communicate complex technical ideas to non-technical stakeholders. Be prepared to discuss your experience working with hybrid teams and your approach to problem-solving and collaboration. Additionally, research the company's mission and values to understand their approach to healthcare and analytics.
Likely Interview Rounds
- 1. Technical~60 min
What to prep: Review data engineering concepts, practice designing data pipelines, and be prepared to discuss data integration and ingestion strategies.
- How do you handle data pipeline failures?
- What data engineering tools have you used in previous roles?
- How do you ensure data quality and integrity in your pipelines?
- 2. System design~60 min
What to prep: Practice system design interviews, focusing on data engineering and analytics systems. Review concepts such as data warehousing, ETL, and data governance.
- Design a data pipeline for a healthcare analytics platform.
- How would you optimize data storage and retrieval for a large-scale analytics system?
- 3. Behavioral~30 min
What to prep: Review the company's mission and values, and be prepared to discuss your experience working with hybrid teams and your approach to problem-solving and collaboration.
- Tell me about a time when you had to collaborate with a cross-functional team to solve a complex data problem.
- How do you handle conflicting priorities and tight deadlines in a data engineering role?
Most Likely Questions
- What is your experience with data engineering tools and technologies?
- How do you stay up-to-date with industry trends and developments in data engineering?
- Can you describe a particularly challenging data engineering project you worked on and your role in it?
Common Pitfalls
- Lack of experience with cloud-based data engineering tools and technologies.
- Inability to communicate complex technical concepts to non-technical stakeholders.
- Insufficient attention to data quality and integrity in pipeline design and implementation.
Free Prep Resources
- • LeetCode
- • System Design Primer (GitHub: donnemartin)
- • Apache Beam documentation