Remote Backend Data Platform Engineer II

jobgether

New York (NY)

A distancia

USD 120.000 - 130.000

Jornada completa

Hace 7 días
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Descripción de la vacante

Jobgether is seeking a Backend Software Engineer II – Data Platform based in the United States. You will build the data platform that powers healthcare products and transform data from health plans, employers, and partners into reliable information.

You will primarily work with Python, taking features from design through production while owning services and technical decisions, solving issues with incomplete, duplicated, or delayed real-world data, and improving reliability, observability, and

Formación

  • Bachelor's degree or equivalent educational background is required.
  • 2+ years of professional backend experience.
  • Proficiency in Python and SQL is expected.
  • Experience building data-intensive backend systems and ETL/ELT pipelines.
  • Familiarity with cloud deployments and API design.

Responsabilidades

  • Build and maintain backend services ingesting and transforming data from partners.
  • Develop systems supporting member identity, eligibility, billing, and integrations.
  • Design APIs, asynchronous workflows and data pipelines used across the organization.
  • Handle incomplete, duplicated, or delayed real-world data with retry/reconciliation logic.
  • Improve reliability, observability, test coverage, and performance of production systems.

Conocimientos

Python
SQL
Distributed systems
ETL/ELT pipelines
Cloud deployment
API design

Educación

Bachelor's degree or equivalent

Herramientas

PostgreSQL
Docker
Kubernetes

Descripción del empleo

Jobgether is seeking a Backend Software Engineer II – Data Platform based in the United States. You will build the data platform that powers healthcare products and transform data from health plans, employers, and partners into reliable information.

You will primarily work with Python, taking features from design through production while owning services and technical decisions, solving issues with incomplete, duplicated, or delayed real-world data, and improving reliability, observability, and

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