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3 дня назад

BI & Data Engineering Team Lead (AI)

Формат работы
hybrid
Тип работы
fulltime
Грейд
lead
Английский
b2
Страна
Israel
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR

BI & Data Engineering Team Lead (Databricks/Snowflake): Leading the BI team to build and own high-impact analytics foundations with an accent on semantic layers, data quality, and scalable data models. Focus on integrating GenAI and agentic workflows to automate development and improve metric governance.

Location: Hybrid in Tel Aviv (3 days a week in office)

Company

hirify.global is an AI-first B2B data platform focused on providing high-quality business intelligence for builders.

What you will do

  • Lead and mentor a team of 4-6 BI Data Engineers, owning the roadmap, architecture, and delivery of the BI platform.
  • Take end-to-end ownership of analytics foundations, transforming raw data into trusted, business-critical insights.
  • Design and govern scalable data models and semantic layers used across Product, GTM, and Finance.
  • Implement GenAI and agentic workflows to automate analytics engineering and increase delivery speed.
  • Drive data quality, performance optimization, and FinOps practices across the data ecosystem.

Requirements

  • 6+ years of experience in Data Engineering or BI roles, with 3+ years in a leadership/management capacity.
  • Must be based in Tel Aviv for a hybrid work model (3 days/week in office).
  • Deep expertise with modern data stacks such as Databricks and/or Snowflake.
  • Advanced proficiency in SQL and Python, including experience with CI/CD and observability.
  • Strong knowledge of dimensional modeling and data warehousing architecture.
  • Proven experience using GenAI tools (e.g., Claude Code) in daily development workflows.

Nice to have

  • Experience leading large-scale data platform migrations.
  • Proficiency with incremental processing patterns and FinOps optimization.

Culture & Benefits

  • AI-first builder culture that values speed and ownership.
  • Collaborative environment focusing on turning ambiguous questions into governed metrics.
  • Monday–Friday work schedule.

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