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7 часов назад

Data Engineer (AI)

150 000 - 175 000$
Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Data Engineer (AI) (Python/SQL): Building scalable data services, pipelines, and models for AI-powered healthcare products with an accent on data quality, large-scale processing, and LLM- and agent-based capabilities. Focus on designing reliable data platforms, optimizing complex queries and storage systems, and supporting clinical, business intelligence, and operational data needs.

Location: New York City, NY; onsite Monday through Thursday with Fridays remote. The role requires onsite presence in the New York City office four days per week and does not provide immigration support.

Salary: $150,000–$175,000 USD annually.

Company

hirify.global develops AI-powered virtual care products, clinical AI, provider-serving agentic solutions, and virtual clinics for health systems.

What you will do

  • Design, develop, and optimize data services and solutions supporting products such as FeatureStore and synthetic data management.
  • Collaborate with data analysts, data scientists, engineers, and cross-functional teams to define requirements and deliver high-quality data solutions.
  • Design and integrate LLM- and agent-based capabilities into data platforms and services.
  • Build and optimize scalable data pipelines and robust data models for clinical, business intelligence, and operational needs.
  • Implement data quality standards, monitoring, and best practices across systems and pipelines.
  • Manage and optimize large-scale data storage and processing systems for reliability and performance.

Requirements

  • 5+ years of experience as a Data Engineer or Backend Engineer, with a strong emphasis on data processing.
  • Proficiency in Python for building services, solutions, data pipelines, automations, and integration tools.
  • Deep SQL experience, including complex queries, performance optimization, and work with large datasets.
  • Strong knowledge of data modeling principles and best practices for relational and dimensional data structures.
  • Commitment to maintaining data quality and trust in business-critical data.

Nice to have

  • Experience with cloud platforms such as AWS, GCP, or Azure for data engineering and storage solutions.
  • Knowledge of data orchestration tools such as Airflow.
  • Understanding of CI/CD practices and version control systems.
  • Experience with Kubernetes.
  • Experience in ML/AI development.

Culture & Benefits

  • Hybrid schedule with onsite work Monday through Thursday and remote work on Fridays.
  • Weekly lunches, a stocked kitchen, monthly social committees, and company events.
  • 18 vacation days, 9 company holidays, 5 sick days, and 2 personal days.
  • Stock options for every full-time employee and paid parental leave.
  • 401(k), commuter benefits, and health, dental, and vision insurance options.

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