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3 дня назад

Senior Software Engineer - Data Engineering

Формат работы
remote (только Europe)
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
Europe
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
Senior Software Engineer - Data Engineering (ETL/ELT and cloud data platforms): Building and maintaining scalable data infrastructure, pipelines, and models that power analytics, reporting, and product features with an accent on data quality, reliability, and observability. Focus on designing production-grade data systems, diagnosing complex data issues, optimizing performance and cost, and supporting incident response.

Location: Remote 100%, Europe only; flexible working hours; no business travel required.

Company

hirify.global is a USA-based software engineering and solutions consulting company delivering high-impact development services to Fortune 500 companies.

What you will do

  • Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and deliver data from internal and external sources.
  • Develop and optimize data models and schemas for analytics, reporting, and downstream product applications.
  • Monitor pipeline health, troubleshoot data quality issues, and implement alerting and observability practices.
  • Partner with analytics, product, and engineering teams to translate data needs into durable solutions.
  • Improve the performance, scalability, and cost-efficiency of data infrastructure.
  • Document technical solutions, contribute to testing, code review, and deployment standards, and participate in on-call or incident response rotations as needed.

Requirements

  • 4+ years of professional experience in data engineering or a closely related discipline.
  • Strong proficiency in SQL and at least one programming language commonly used for data engineering, such as Python, Scala, or Java.
  • Hands-on experience building and operating ETL/ELT pipelines in a production environment.
  • Experience with cloud data platforms such as AWS, GCP, or Azure.
  • Experience with modern data warehousing tools.
  • Solid understanding of data modeling, data quality, and pipeline orchestration concepts.
  • Ability to work with large, complex datasets and diagnose data issues independently.

Nice to have

  • Experience with orchestration tools such as Airflow, Dagster, or similar.
  • Familiarity with streaming data technologies such as Kafka or Kinesis.
  • Experience with dbt or similar transformation frameworks.
  • Exposure to infrastructure-as-code practices such as Terraform.
  • Prior experience supporting analytics or data science teams directly.

Culture & Benefits

  • Competitive compensation with benefits, paid vacation, and sick leave.
  • Globally diverse engineering team working on challenging engineering problems.
  • Remote-first and ultra-flexible working conditions with flexible working hours.
  • Generous home-office equipment allowance and access to a nearby office or coworking facility.
  • Start-up work environment with opportunities for professional growth and development.

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