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2 часа назад

Experienced Software Engineer, GeoTech Team (Python)

Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
c1
Страна
Israel
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
Experienced Software Engineer, GeoTech Team (Python): Building data pipelines, infrastructure, and Python services that process and structure subsurface utility data with an accent on data quality, orchestration, and scalable processing. Focus on designing ETL workflows, implementing CI/CD for data systems, integrating AI development tools, and maintaining reliable mapping applications.

Location: Tel Aviv, Israel

Company

A growing startup building technology to map subsurface infrastructure and provide reliable, real-time utility data for the construction industry.

What you will do

  • Design and implement backend software solutions for the GeoTech team.
  • Process and structure incoming data to support an accurate, up-to-date utilities map.
  • Build and manage ETL workflows, databases, and data infrastructure components.
  • Develop and optimize complex Python applications and services for efficient data processing.
  • Design CI/CD processes for data processing, releases, testing, and monitoring.
  • Collaborate with product managers, designers, QA engineers, and other team members while providing technical guidance.

Requirements

  • 3–5 years of software engineering experience with solid Python skills.
  • Experience with AI development tools; Claude Code is used daily.
  • Familiarity with Airflow or comparable orchestration tools.
  • Experience with PostgreSQL or SQL, AWS services, Kubernetes, Docker, and debugging.
  • Fluent written and verbal English.
  • Curiosity and motivation to develop an AI-first engineering workflow.

Nice to have

  • Interest in maps or direct GIS experience.
  • Civil engineering experience.
  • Experience with message queues, ArgoCD, Helm, or KEDA in Kubernetes environments.

Culture & Benefits

  • AI-first engineering culture with daily use of AI development tools.
  • Collaborative work across product, design, and QA functions.
  • Focus on technical quality, maintainability, monitoring, and reducing technical debt.

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