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Data Engineer Analyst (AWS)

Формат работы
remote (только Mexico)
Тип работы
fulltime
Грейд
middle
Английский
c1
Страна
Mexico
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 Analyst (AWS): Designing and implementing scalable, domain-oriented data solutions for high-impact enterprise initiatives with an accent on batch and streaming ingestion pipelines. Focus on building reliable data models, ensuring data quality, and leveraging AI-assisted tools to optimize performance and productivity.

Location: Must be based in Mexico

Company

hirify.global is a premier AI services provider that aligns human expertise with artificial intelligence to drive innovation and meaningful impact for global clients.

What you will do

  • Design and develop scalable data pipelines using AWS services like Glue, S3, and Athena.
  • Build and optimize batch and streaming ingestion pipelines, including CDC-based architectures.
  • Implement data models aligned with business and analytics requirements.
  • Ensure high data quality, reliability, and performance across all datasets.
  • Collaborate with cross-functional teams to align technical solutions with business needs.
  • Apply best practices in modular design, reusability, and data governance.

Requirements

  • 3+ years of experience in Data Engineering or related disciplines.
  • Advanced English proficiency for effective communication with global teams.
  • Hands-on experience building and maintaining data pipelines on AWS.
  • Ability to design and implement AI/automation Proof of Concepts.
  • Experience with document management workflows and structured output generation.
  • Must be based in Mexico for 100% remote work.

Culture & Benefits

  • Private healthcare and at-home medical assistance programs.
  • Savings incentive program with company matching contributions.
  • Educational loans and subsidies for professional development.
  • Work-life balance perks including Family Day and graduation leave.
  • Collaborative environment focused on AI-driven innovation.

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