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8 дней назад

Analytics Engineer (FinTech)

Формат работы
remote (только Europe)/hybrid
Тип работы
fulltime
Грейд
junior
Английский
b1
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
Analytics Engineer (SQL/Python/AI): Building a trusted analytics data layer with an accent on dimensional data modeling, metric standardization, data quality, and semantic layers. Focus on orchestrating transformations, defining reliable business metrics, and preparing governed data for internal AI and LLM use cases.

Location: Multiple locations across Europe; hybrid or remote work model depending on location.

Company

hirify.global is a fast-growing global FinTech providing digital payment solutions through an international team and offices across Europe.

What you will do

  • Design and develop the analytics data layer, including data marts, dimensional models, star schemas, business entities, and metric definitions.
  • Build and maintain SQL and Python transformations orchestrated with Airflow or similar tools.
  • Develop the Looker semantic layer and create consistent definitions for metrics and dimensions.
  • Implement data quality checks, freshness and completeness monitoring, alerts, documentation, and lineage.
  • Collaborate with business teams, analysts, and data engineers to translate requirements into reliable data models.
  • Use AI tools to improve development, testing, documentation, and internal LLM use cases.

Requirements

  • At least 2 years of hands-on experience in analytics engineering or a similar data role.
  • Strong SQL skills, including CTEs, window functions, query optimization, and execution plans.
  • Experience with analytical data modeling, including Kimball, slowly changing dimensions, facts, and dimensions.
  • Solid Python skills, plus experience with Airflow or similar orchestration tools.
  • Experience with BI tools, Git, code review, and basic Linux/Bash.
  • English at B1 level or higher, with confidence collaborating with business stakeholders.

Nice to have

  • LookML, dbt, semantic layers, or data quality and observability tools.
  • Experience setting up AI agents, repository instructions, or MCP connections to data warehouses and BI tools.
  • Kafka, NoSQL/Elastic, or experience reading PHP source code.

Culture & Benefits

  • Work remotely or in a hybrid setup depending on location, with flexibility and autonomy.
  • Collaborate with a 500+ international team across four offices.
  • Access the internal Academy, relevant training, and external learning support.
  • Take ownership of professional growth and contribute to digital finance products.

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