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Sidecar Health is transforming health insurance by making excellent healthcare affordable and accessible. This Staff-level role owns the data platform that powers the company's operations—the pipelines that ingest provider directories, benefit and pricing feeds, and claims data from disparate systems, land them in Snowflake, and deliver them back out to third-party partners via SFTP.
You will be responsible for designing and maintaining integrations with third-party data providers, handling schema drift, malformed data, and partner-specific quirks gracefully. You'll build internal tools that automate repetitive operational workflows—for example, automating pricing adjustments for benefit amounts across large provider datasets, turning manual processes into scalable, self-service systems that operations and pricing teams can use without engineering intervention.
As a Staff engineer, you'll set technical direction for how the company handles data at scale, evaluate and introduce modern architectural approaches (event-driven pipelines, CDC, workflow orchestration), and act as a technical unblocker across teams. You'll review designs, pair on hard problems, mentor other engineers, and help them ship. You'll also drive engineering standards for data pipeline reliability, observability, and testing, and partner closely with product, operations, and pricing stakeholders to translate ambiguous business needs into durable technical systems.
The role demands strong fundamentals in distributed systems, data modeling, and modern architectural patterns. You'll need to operate with comfort in ambiguity, taking loosely defined operational pain points and turning them into well-scoped technical solutions. Strong communication skills are essential—you'll explain data architecture tradeoffs to both engineers and non-technical stakeholders. The company values bias for action, ownership, pragmatism, and resilience in a startup environment.
**Requirements:**
- 10+ years of professional software engineering experience with a track record of owning data-intensive systems in production
- Deep experience building and operating data pipelines at scale (ingestion, transformation, delivery); Snowflake experience strongly preferred
- Hands-on experience building and maintaining third-party integrations, including handling unreliable or inconsistent external data
- Experience building internal tools/platforms that automate operational workflows for non-engineering teams
- Strong fundamentals in distributed systems, data modeling, and modern architectural patterns for processing data at scale
- Demonstrated ability to operate as a technical leader: setting direction, unblocking others, and influencing without direct authority
- Comfort with ambiguity and ability to translate loosely defined operational pain points into well-scoped technical solutions
- Strong communication skills; able to explain data architecture tradeoffs to both engineers and non-technical stakeholders
- Fluent, disciplined use of AI-assisted tooling to move faster, with the rigor to verify correctness, security, and quality before shipping
**Nice to haves:**
- Experience with healthcare data (provider directories, NPI, claims, fee schedules, or benefits data)
- Familiarity with workflow orchestration tools (Airflow, dbt, Step Functions, etc.)
**Geographic requirement:** Must be based in California, Oregon, or Washington.
