Staff Software Engineer, Full Stack

New

Sidecar HealthHealth Insurance

MUST BE BASED IN CALIFORNIA, OREGON OR WASHINGTONFull-TimeStaff

SalaryCompetitive salary, bonus opportunity, and equity package

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Job Details

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, including ingestion, transformation, and delivery.
Hands-on experience building and maintaining third-party integrations, including handling unreliable or inconsistent external data.
Experience building internal tools or 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 and influencing without direct authority.
Comfort with ambiguity and ability to turn loosely defined pain points into well-scoped technical solutions.
Strong communication skills with the ability to explain architectural tradeoffs to both technical and non-technical stakeholders.
Fluent, disciplined use of AI-assisted coding tools with rigorous verification for correctness and security.
Snowflake experience is strongly preferred.
Experience with healthcare data (e.g., provider directories, NPI, claims) is a plus.
Familiarity with workflow orchestration tools like Airflow, dbt, or Step Functions is a plus.

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, 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, evaluating and introducing modern architectural approaches like event-driven pipelines and CDC.
Act as a technical unblocker across teams by reviewing designs and pairing on complex problems.
Drive engineering standards for data pipeline reliability, observability, and testing.
Partner with product, operations, and pricing stakeholders to translate ambiguous business needs into durable technical systems.
Mentor engineers through code review, design documentation, and hands-on collaboration.

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