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Data & Insight Manager (iGaming)

Тип работы
fulltime
Грейд
lead
Английский
b2
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 & Insight Manager (Data Analytics): Building and operating a data product capability to enable scalable and actionable insights with an accent on bridging business needs with data platform capabilities. Focus on defining the data product roadmap, implementing a Data-as-a-Product operating model, and ensuring rigorous data governance and quality.

Company

hirify.global is a company operating transactional platforms, likely within the iGaming and Fintech domains.

What you will do

  • Define and own the data product roadmap, translating business requirements into scalable data solutions.
  • Lead and develop a cross-functional team comprising Analysts, Engineers, Architects, and Scientists.
  • Establish and enforce a Data-as-a-Product operating model to drive clarity in roles and ways of working.
  • Act as the primary interface between data teams and stakeholders across Commercial, Product, Finance, Risk, and Technology.
  • Define data ownership, enforce accountability, and establish data quality and trust frameworks.
  • Manage the backlog to balance immediate reporting needs with long-term platform investments.

Requirements

  • 5–10+ years of experience in data and analytics, with at least 3+ years in a leadership or management capacity.
  • Proven experience owning end-to-end delivery of data initiatives from requirements to adoption.
  • Experience managing cross-functional data teams.
  • Solid understanding of ETL/ELT pipelines, data modeling (fact/dimension, semantic layers), and lakehouse concepts.
  • Strong stakeholder management skills with the ability to influence business and technology teams.

Nice to have

  • Experience in iGaming, fintech, or other transactional platforms.
  • Familiarity with modern data stack tools such as Snowflake, BigQuery, dbt, and Airflow.
  • Experience with API-driven, event-based, or real-time data processing systems.
  • Exposure to supporting or enabling AI/ML initiatives.
  • Background spanning both technical and business-facing roles.

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