Founding Data Engineer
Lotus Health Ai
Data Science
San Francisco, CA, USA
USD 180k-220k / year + Equity
Posted on Dec 15, 2025
Location
Lotus Health San Francisco
Employment Type
Full time
Location Type
On-site
Department
Engineering
Founding Data Engineer
Location: San Francisco (On-site)
Compensation: $180,000 – $220,000 + variable equity based on cash compensation
Technologies: Python, Pydantic, PostgreSQL, Linux, AWS, DuckDB, Modal
About Us
Lotus Health is a groundbreaking primary care app that integrates your medical records, AI, and real doctors to provide free, personalized healthcare and prescriptions.
Our team includes ex-founders and engineers who have built and scaled consumer apps to millions of users, generating over $100M in annual revenue. Lotus is backed by Kleiner Perkins, and clinicians at Harvard and Stanford.
Role Overview
We’re looking for a founding Data Engineer to help design, simplify, and scale Lotus’s health data infrastructure from the ground up. You’ll work closely with the founding team to unify fragmented data systems, improve data correctness and traceability, and deliver fast, accurate, and explainable information to our AI and clinician agents.Your work will directly impact how medical knowledge is surfaced, validated, and applied in real-world care. This is a rare opportunity to join early, shape the core data foundation, and help define the future of accessible, intelligent healthcare.
Responsibilities
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Knowledge Base and Search Improvements
Improve knowledge bases so that citations resolve to original data and searches are fast, relevant, and prioritize tier-one medical information.
Continuously enhance retrieval accuracy and data lineage tracking.
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Data Ingestion and Integrity
Rebuild data pipelines to eliminate stale data, support clinician and patient corrections, and ensure full traceability.
Design models that sync cleanly with health data partners and credentialing authorities.
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Observability and Analytics
Build monitoring and analytics for background jobs to monitor failure rates and identify partner vs. internal issues.
Streamline tracing, logging, and auditing to reduce redundancy while maintaining compliance-grade visibility.
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Data Portability and Compliance
Enable seamless data migration between Lotus deployments with proper cache handling and deletion workflows.
Safeguard integrity and privacy during transfers.
What You Bring:
Strong proficiency in Python and SQL
Proven experience with system refactors, schema migrations, and data infrastructure simplification
Familiarity with PostgreSQL (including JSONB and vector types) and AWS
Experience building scalable systems (10K+ users)
Comfort working across the stack, from schema design to production debugging
Curiosity, pragmatism, and a willingness to deeply understand complex data flows
Bonus Points:
Experience with FastAPI, SQLAlchemy, DuckDB, Temporal, ClickHouse, Valkey, or similar systems
Knowledge of logging/monitoring stacks (Sentry, Langfuse) and containerized deployments (Docker, ECS)
Experience simplifying multi-layered data systems where architectural issues cascade through storage, logging, and application layers
Strong intuition for designing systems that balance correctness, observability, and performance
Why Lotus:
Join a team redefining how healthcare data is understood and acted upon. You’ll work with a world-class group of engineers, clinicians, and AI researchers to build something with lasting impact — accessible, free primary care for everyone.
As the first Data Engineer on a small, exceptional team you’ll have the autonomy to build the foundation and see your work directly influence patient care at scale.