Staff Software Engineer - Data [NYC or SF]
Amigo
Get more replies from employers
Send a job-specific resume in minutes.
Benefits offered by this job
Job summary
Amigo is seeking a Staff Data Engineer to own the data layer that powers healthcare AI solutions. You will ingest data from EHRs, schedulers, and warehouses, keep it current, and unify records into a single patient/provider view.
You’ll own ingestion, transformation, modeling, and the query tools used by teams. You will design and optimize data pipelines, ensure data freshness, and enable powerful query interfaces over secure healthcare data.
Qualifications
- Built production data platforms that ingest, process, and serve data at scale.
- Designed scalable streaming and batch pipelines for production systems.
- Deep expertise in SQL and distributed query optimization.
- Hands-on experience with modern data platforms (Databricks, Snowflake, Delta Lake, Iceberg, Spark, Kafka).
- Experience with event-driven architectures and change data capture (CDC).
- Connector frameworks or ingestion platforms interfacing with enterprise data sources.
Responsibilities
- Ingest data from EHRs, schedulers, warehouses, and APIs and keep it current.
- Transform and model data to a single, accurate patient/provider view.
- Build and optimize data pipelines ensuring data freshness and reliability.
- Enable natural language query interfaces over healthcare data.
- Own data modeling, query performance, and operational reliability.
Skills
Education
Tools
Job description
Amigo partners with healthcare organizations to deploy robust AI infrastructure that directly serves patients and providers. Our agents handle clinical workflows and patient engagement across the entire journey: pre-visit intake, care navigation, post-visit care plans, patient monitoring, and more.
Amigo partners with healthcare organizations to deploy robust AI infrastructure that directly serves patients and providers. Our agents handle clinical workflows and patient engagement across the entire journey: pre-visit intake, care navigation, post-visit care plans, patient monitoring, and more.
We're fresh off our Series A backed by Tier 1 investors like Madrona, General Catalyst, and Optum Ventures. Our work is validated with leading academic medical institutions. Our agents have reached 3M+ patient encounters and are on track to 10x this year.
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
- 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
- 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
- Comprehensive health, dental, and vision insurance
- Daily catered lunch and dinner
- Mental health support and wellness coaching
- Flexible wellness stipend for fitness, therapy, or personal growth
- Annual learning budget for courses, books, or conferences
- Conference attendance budget for professional development
- Annual team offsite
- Academic collaboration opportunities
- Unlimited PTO
- Patients Win, We Win
- High Standards, High Care
- Thoughtful Urgency
- Intensely Measured
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.
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.
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.
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.
- Low ego: Politics and territory don't interest you. The best ideas win, regardless of who has them.
- Direct: You say the hard thing, challenge ideas openly, and commit fully once decided.
- High agency: You thrive on trust rather than instruction. When you see something is broken, you fix it. You don’t file tickets and wait for someone else.
- Bar of excellence: You hold yourself to a bar most people wouldn't, and you want teammates who do the same.
- Skeptical: You push back on rules that don’t make sense and question assumptions that haven’t earned their place.
Compensation Range: $260K - $300K
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
