Staff Software Engineer - Data [NYC or SF]

As a Staff Data Engineer at Amigo, you’ll build the data layer everything else runs on. Healthcare organizations already keep their data in EHRs, schedulers, and warehouses. Your job is to pull that data in, keep it current, and turn scattered records into one accurate picture of each patient and provider. If the data is wrong or stale, everything above it breaks, so correctness is the work, not a nice-to-have. You’ll own it end to end: ingestion, transformation, modeling, and the query tools teams use., * Building integrations that ingest and sync customer systems (EHRs, schedulers, warehouses, APIs)

• Designing transformations that turn messy source data into one normalized model
• Building and optimizing data pipelines that keep one clean profile per patient
• Powering natural language query interfaces over healthcare data
• Owning data modeling, query performance, and data freshness at scale

What we’re looking for

• Built and operated production data platforms that ingest, process, and serve millions of events with high reliability
• Designed scalable streaming and batch pipelines, data models, and ETL/ELT workflows for production systems
• Possess deep expertise in SQL, distributed query optimization, and large-scale data processing
• Have hands-on experience with modern data platforms such as Databricks, Snowflake, Delta Lake, Apache Iceberg, Spark, Kafka, or similar technologies
• Designed event-driven architectures, change data capture (CDC), online serving systems, or reverse ETL pipelines
• Built connector frameworks or ingestion platforms that integrate enterprise applications and third-party data sources
• Balance performance, scalability, cost, and operational simplicity when designing distributed systems
• Own production systems end-to-end, including architecture, implementation, monitoring, reliability, and incident response
• Value simple, maintainable solutions, communicate directly, and maintain a high engineering bar with a low-ego, collaborative approach
• You can work on site in New York City or San Francisco, * Daily catered lunch and dinner
• Mental health support and wellness coaching
• Flexible wellness stipend for fitness, therapy, or personal growth

Growth & Development

• Annual learning budget for courses, books, or conferences
• Conference attendance budget for professional development
• Annual team offsite
• Academic collaboration opportunities
• Unlimited PTO

• Experience building data platforms in regulated or high-reliability industries such as healthcare, financial or services
• Familiarity with healthcare data standards such as FHIR, HL7, or other clinical interoperability frameworks
• Experience building data platforms that power production AI, machine learning, or agentic applications
• Familiarity with modern lakehouse technologies such as Delta Lake, Apache Iceberg, or Unity Catalog
• Experience with streaming platforms, change data capture (CDC), or event-driven architectures
• Experience operating large-scale data platforms with a focus on reliability, observability, and cost efficiency

3.83.8 out of 5 stars San Francisco, CA $260,000 - $300,000 a year - Full-time, Pulled from the full job description

• Vision insurance
• Dental insurance
• Unlimited paid time off

• Patients Win, We Win If patients aren’t getting better care, we haven’t earned the right to scale. Every internal decision gets pressure-tested: does this make patients’ lives better? If we can’t draw the line, we question why we’re doing it.

• High Standards, High Care We hold a high bar for the team because patients are counting on us to get this right. But high standards only work with genuine investment in each other. You can take risks, admit mistakes, and challenge ideas-not despite our standards, but because of them.

• Thoughtful Urgency We move fast by default, but speed without judgment is recklessness. The discipline is knowing which decisions are reversible vs. not. In healthcare AI, the companies that win will be fast everywhere they can be and careful everywhere they must be. We build the muscle to do both.

• Intensely Measured We instrument patient outcomes, provider ROI, system performance, and clinical accuracy. But data without action is surveillance. Every metric should have an owner, a threshold, and a response plan. If we’re measuring something but never acting on it, we stop measuring it.