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Sobre este puesto de Data Engineer en Tennr

Tennr · Híbrido · New York City Office

Company Description

Today, when you go to your doctor and get referred to a specialist, your doctor sends out a referral and tells you, “They’ll be in touch soon.” So you wait. And wait. Sometimes days, weeks, or even months. Why? Because too often providers are overwhelmed with the painstakingly tedious work required to get paid by insurance companies. Powered by proprietary models, Tennr handles the complex paperwork that gets patients through the door and providers paid, helping operators get patients the right care, at the right time, in the right setting.

 

Role Description

  • Own the data engineering function end-to-end: build and maintain production pipelines from Tennr's application into Snowflake, ensuring reliability and performance at scale.

  • Lead EHR discovery and integration initiatives across ~5–10 healthcare systems. Understand what data is available, what integrations we have, evaluate technical tradeoffs, and build creative solutions to extract and ingest data into Snowflake.

  • Own Snowflake as our strategic data platform: architect instance setup, implement security best practices and governance, manage vendor relationships, and ensure zero data exposure.

  • Design and implement data models that transform raw data into usable assets. Surface and safely share that data across Tennr so internal teams can build their own analytics and tooling.

  • Implement comprehensive monitoring and alerting to detect pipeline issues quickly and resolve them with minimal business impact.

  • Explore innovative approaches to structure and extract insights from unstructured referral documentation, including potential AI-enabled models to unlock value from clinical text data.

Candidate Qualifications

  • 3–5 years of experience in data engineering, with a strong track record of building and maintaining scalable data pipelines and infrastructure.

  • Proven expertise with Snowflake and modern cloud data platforms (e.g., AWS, GCP); hands-on experience with data pipeline tools and orchestration frameworks.

  • Strong understanding of healthcare data—claims, EHR systems, and data integration patterns—or demonstrated ability to quickly learn complex domain-specific systems.

  • Healthcare-data security awareness and familiarity with best practices (e.g., HIPAA considerations, data governance, compliance) is a strong plus.

  • Excellent problem-solving skills and comfort with complex, ambiguous integration challenges—not just standard connector configuration.

  • Outstanding communication skills, capable of articulating complex technical and healthcare concepts to a diverse audience.

  • A team player who thrives in collaborative environments and values diverse perspectives.

  • Prior experience in a startup or fast-paced tech environment is a plus.

Why Tennr?

  • Drive Impact: one of our company values is Cowboy, meaning you set the pace. You won’t just talk about things, you’ll get them done. And feel the impact.

  • Develop Operational Expertise: learn the inner workings of scaling systems, tools, and infrastructure

  • Innovate with Purpose: we’re not just doing this for fun (although we do have a lot of fun). At Tennr, you’ll join a high-caliber team maniacally focused on reducing patient delays across the U.S. healthcare system.

  • Build Relationships: collaborate and connect with like-minded, driven individuals in our Hudson Square office 4 days/week

  • Free lunch! Plus a pantry full of snacks.

 

Benefits

  • Beautiful new office at 345 Hudson Street

  • Unlimited PTO

  • 100% paid employee health benefit options

  • Employer-funded 401(k) match

  • Competitive parental leave

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Cómo se compara este salario de Data Engineer

Este puesto paga $175,000/yr — en línea con el rango típico para los puestos de Data Engineer.

$100,000 la mediana de $160,000 $242,540

Rango típico $126,800–$197,582/yr, a partir de 1,658 ofertas comparables de Data Engineer en JobsRadar (salario anualizado en USD). Ver datos salariales de Data Engineer →

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