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# Staff Software Engineer

- **Company:** Sidecar Health
- **Location:** Long Beach, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Architectural Patterns, Code Review, Data Architecture, Data Infrastructure, Software Design Documents, Distributed Systems, Software Engineering, Data Processing, File Transfer Protocol (FTP), Snowflake, Integration Frameworks, Data Pipelines
- **Published:** October 1, 2026
- **Apply:** https://www.juju.com/job/16_d7ba3293

## About the Role

* 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, and 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; you can take a loosely defined operational pain point and turn it into a well-scoped technical solution
 * Strong communication skills; able to explain a data architecture tradeoff 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 it ships

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.)

## Description

Healthcare runs on data moving between systems that were never designed to talk to each other. Provider directories, benefit and pricing feeds, claims data, and a long tail of third-party partners each with their own format and quirks. You'll own the platform that makes that data usable: the pipelines that land it in Snowflake, the delivery pipelines that gets it back out to partners, and the third-party integrations that keep it flowing correctly at scale.

You'll also build the internal tools that let our operations and pricing teams move fast without waiting on engineering for every change. Things like automating pricing adjustments for benefit amounts across large provider datasets, so repetitive manual work becomes a self-serve, auditable workflow.

This is a Staff-level role. You'll be expected to set technical direction for how we handle data at scale, unblock other engineers who are heads-down on features, and be the person the team turns to when a data pipeline or integration problem doesn't have an obvious answer.

**MUST BE BASED IN CALIFORNIA, OREGON OR WASHINGTON**

What You'll Do

 * Own and evolve the data pipeline platform that ingests provider, benefit, and pricing data and delivers it into Snowflake and out to third-party consumers via SFTP
 * Design, build, and maintain integrations with third-party data providers and vendors, handling schema drift, malformed data, and partner-specific quirks gracefully
 * Build internal staff tools that automate repetitive, high-volume operational work (e.g., pricing adjustments for benefit amounts) - turning manual processes into scalable, self-service systems
 * Process and reconcile large volumes of medical provider data, with an eye for data quality, lineage, and auditability
 * Set technical direction for data infrastructure and integration patterns - evaluate and introduce modern architectural approaches (event-driven pipelines, CDC, workflow orchestration, etc.) where they solve real problems
 * Act as a technical unblocker across teams: review designs, pair on hard problems, and help other engineers ship rather than stall
 * Drive engineering standards for data pipeline reliability, observability, and testing
 * Partner closely with product, operations, and pricing stakeholders to translate ambiguous business needs (like "automate this pricing process") into durable technical systems
 * Mentor engineers and raise the technical bar through code review, design docs, and hands-on collaboration