Data Engineer

Tono Health builds software and operates specialty care clinics, starting with dermatology. The Data Engineer will build and maintain data pipelines and trusted datasets across clinical, operational, billing, and AI workflows, with attention to data quality, observability, and privacy.

Responsibilities

• Building and maintaining ingestion pipelines (dlt, Prefect) from our Postgres application database, Stripe, Posthog and other sources into our warehouse (BigQuery, Motherduck/DuckDB)
• Modeling clean, well-tested datasets in dbt, covering patient funnels, clinical operations, scheduling, billing and revenue
• Building the datasets that feed our AI work, such as labeled data, evaluation sets and clinician-feedback pipelines
• Digging into data to answer questions like where patients drop off in intake, or what slows a visit down
• Adding tests, freshness checks, lineage and alerting so the team can trust what they see
• Handling PHI carefully, with access controls, de-identification and audit trails suited to a regulated environment
• Working with engineers on schema changes and backfills so analytics doesn't break when the product moves

Preferred

• experience with healthcare or other regulated data (HIPAA, EHR data), DuckDB, dlt, TypeScript, supporting ML or AI teams with training and evaluation data, or working at a startup
• Healthcare Data
• Regulated Data
• HIPAA
• EHR Data
• DuckDB
• dlt
• TypeScript
• ML/AI Data Support
• Training Data
• Evaluation Data
• Startup Experience

Benefits

• Meaningful equity in a high-growth, venture-backed company
• Medical, dental, and vision coverage
• Direct access to founders and an agile team where your impact is highly visible. We do weekly demos with leadership
• Unlimited PTO to recharge when you need it
• Hybrid work, currently a few days per week in the DUMBO, Brooklyn office
• Fully remote considered for the right candidate

Company

• AI-native platform for specialty dermatology care
• New York, New York, USA
• https://tonohealth.com/
• Founded in 2020
• 11-50 employees

Qualifications

• 3+ years experience building and operating production data pipelines
• Strong SQL and solid Python
• Experience with a modern data stack: dbt, an orchestrator such as Prefect or Airflow, and a cloud warehouse such as BigQuery or Snowflake
• Good relational database fundamentals, including schema design, migrations and query performance (we use Postgres)
• A habit of testing and monitoring your pipelines, and caring whether the numbers are right
• Ability to turn a vague question from a doctor or operator into a clear dataset
• Comfort working in a fast-moving team and picking up whatever the system needs
• Care about privacy and data quality, and take pride in your craft
• Experience with healthcare or other regulated data (HIPAA, EHR data), DuckDB, dlt, TypeScript, supporting ML or AI teams with training and evaluation data, or working at a startup

Required skills

• Airflow, BigQuery, Dbt, PostgreSQL, Prefect, Production Data Pipelines, Python, Query Performance, SQL, Schema Design, Snowflake

Experience

• 3+ years