Data Engineer, ETL

🏢 Trovohealth · 📍 New York 💰 $170 - $250,000 / yr

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Position Summary & Responsibilities

About us

Thesis is building the AI-powered care team platform for infinitely scalable clinical capacity. We radically increase access and improve quality of care by combining AI agents with clinical experts to take on high-impact clinical operations and care management activities for healthcare organizations.

We’re based in NYC, are growing rapidly, and are backed by $60 million in funding from Oak HC/FT, CRV, Black Opal Ventures, and experienced C-level healthtech angel investors.

About the role

We are looking for a highly driven Data Engineer to help design, build, and scale the data foundations that power Thesis’s AI agents, including owning critical client integrations. You will work closely with the product, engineering, and AI/ML teams to ensure Thesis’s data architecture is scalable, reliable, secure, and actionable. This is a broad-scope, high-impact role for a technical builder who thrives in ambiguity and wants meaningful ownership over modern data infrastructure in an early-stage healthcare startup.

Responsibilities

Build core data infrastructure: Design, implement, and maintain scalable, data pipelines and architectures across ingestion, transformation, and storage layers
Own client integrations and data ingestion: Structure and maintain durable integrations and ETL workflows to reliably onboard and normalize client data.
Design robust data models: Build and maintain clean, well-documented data models that support reporting, analytics, and downstream automation.
Enable product and analytics outcomes: Ensure data flows accurately from source systems to products, analytics, and AI/ML use cases.
Drive data quality and reliability: Implement monitoring, testing, and observability to ensure high data quality and system uptime.

We expect you to have:

Strong technical foundation: 4-6+ years of experience in Data Engineering or Software Engineering with a data focus; strong proficiency in Python and SQL.
Modern data stack experience: Hands-on experience with cloud data platforms (AWS and/or GCP), data warehouses (Snowflake, Redshift, or BigQuery), orchestration tools (Airflow or similar), and transformation tools (dbt preferred).

🎯 Candidate Preparation Guide For Trovohealth Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Assessment centers on mission-driven dedication to healthcare innovation, data privacy compliance, and agile problem-solving in a fast-growing digital health space.

📋 Preparation Priorities (Key Areas to Clarify):

1. Treating patient data security or compliance frameworks as secondary metrics
2. Showing impatience or frustration when dealing with the slow adoption cycles inherent to healthcare
3. Lacking data literacy when evaluating health tech outcomes

✨ Recommended Role Alignment Hook:

I scale digital health innovations that bridge clinical efficacy with exceptional user experience, always keeping security and compliance foundational.

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