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Staff Data EngineerInterWell Health • New York, New York, United States
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Staff Data Engineer

InterWell Health
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

Interwell Health is a kidney care management company that partners with physicians to reimagine healthcare, setting the standard for the industry and helping patients live their best lives.
What You’ll Do Architecture & Strategy
Design and evolve a scalable, secure, cloud-native lakehouse platform leveraging Databricks, Microsoft Fabric (OneLake, Lakehouse, Data Factory), and dbt.
Define modeling patterns, governance frameworks, and engineering best practices across the data lifecycle.
Lead design reviews and guide teams in adopting scalable architectural patterns.
Drive long‑term platform strategy and evaluate emerging technologies.
Hands‑on Engineering
Design and implement batch and streaming data pipelines for healthcare data sources (EHR, claims, HL7/FHIR, APIs, flat files, databases).
Develop modular ingestion, quality, lineage, metadata, and observability frameworks that scale across domains.
Produce clean, analytics‑ready datasets and data models for BI, analytics, and machine learning workloads.
Implement HIPAA‑aligned access patterns and secure handling of PHI.
Architect Databricks workloads (clusters, jobs, Unity Catalog, Delta Lake) for reliability, performance, and cost efficiency.
Integrate Databricks and Microsoft Fabric with Azure services and enterprise systems.
Partner with product managers, data scientists, analysts, clinicians, and business stakeholders to translate healthcare data needs into scalable solutions.
Lead cross‑functional initiatives that modernize and unify the organization’s data ecosystem.
Mentor senior and mid‑level engineers; elevate team capability through technical coaching and standards.
Drive roadmap planning, platform evolution, and long‑term data strategy.
Champion engineering excellence, reliability practices, documentation quality, and governance.
What You’ll Need
Bachelor’s degree in Computer Science, Engineering, or a related field.
7+ years of experience in data engineering.
2+ years operating in a senior or staff‑level engineering role.
Deep hands‑on proficiency with Databricks, Spark, Delta Lake, dbt, and Python.
Proven ability to design and operate large‑scale cloud data platforms (Azure preferred).
Hands‑on experience with Data Engineering, Data Factory, Lakehouse, OneLake.
Advanced data platform architecture and lakehouse design expertise.
Demonstrated ability to design modular, extensible frameworks and guide the long‑term evolution of enterprise data platforms.
Strong command of distributed data processing and cloud‑native engineering.
Experience working in HIPAA‑regulated environments and handling PHI.
Healthcare data fluency, including regulated data handling and compliance.
Technical leadership, mentorship, and influence across teams.
Strong communication skills with both technical and clinical stakeholders.
Experience with platform reliability, CI/CD for data pipelines, and infrastructure as code.
100% remote; ET or CT work hours preferred.
Preferred
Experienced in implementing and supporting Epic integrations, leveraging Cogito Cloud and Caboodle data models, and delivering reliable incremental data pipelines from Caboodle/Clarity.
We are committed to diversity, equity, and inclusion throughout our recruiting practices. Everyone is welcome and included. We value our differences and learn from each other. No matter how you identify, we value everyone’s unique journey.
As set forth in Interwell Health’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
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  • New York, New York, United States

Sprachkenntnisse

  • English
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