Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Чётко очерченная руководящая роль в продуктовой SaaS-компании с ответственностью за ключевую платформу данных и развитием команды; обязательные визиты в офис в Хельсинки ограничивают гибкость по локации.
?Офис в Хельсинки
Актуальный стек данных
Понятная зона ответственности
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Engineering Manager, Connectors & Data Factory (Data Engineering/AI): Leading a six-person team building and operating a platform that ingests customer data from enterprise source systems and transforms it into a common data model with an accent on delivery ownership, team development, and technical health. Focus on guiding architecture and reliability decisions, improving development workflows with AI-assisted development, and coordinating complex data integration needs across engineering and product teams.
Location: Helsinki, Finland. Flexible hybrid work is available, with attendance at the Helsinki office required at least once a week.
Salary: EUR 6,600–7,600 per month, with higher compensation possible for particularly senior profiles.
Company
hirify.global is a Finnish procurement analytics SaaS company that helps large enterprises analyze procurement data, optimize spend and supply chains, reduce emissions, and improve resilience.
What you will do
Lead the six-person Connectors & Data Factory team and own delivery priorities, planning, dependencies, risks, reliability, capabilities, and technical debt.
Hire, coach, support career growth, provide feedback, and handle performance issues.
Guide technical decisions, architectural discussions, maintainability, testing, security, and team ways of working.
Partner with the product manager, Data Engineers, and product teams to turn platform needs into deliverable plans and make informed trade-offs.
Improve shared engineering practices and contribute to engineering-wide decisions with other leaders.
Requirements
Experience leading engineering teams, including hiring, coaching, and supporting people through difficult performance situations.
Engineering background with experience in data engineering, including extracting, transforming, and operating data from multiple source systems.
Ability to participate in architecture discussions, challenge assumptions, and balance delivery needs with reliability and maintainability.
Good judgment in ambiguous situations, with the ability to make thoughtful trade-offs, explain decisions, and adapt as information changes.
Practical experience improving development workflows and adopting new tools and practices, including AI-assisted development.
Hands-on understanding of AI capabilities and limitations, sufficient to guide adoption and make informed decisions without owning delivery-critical implementation.
Clear, thoughtful communication in English, including explaining technical decisions to non-engineering stakeholders and aligning engineering, product, and business teams.
Nice to have
Experience with enterprise ERP systems such as SAP, Oracle, NetSuite, or Microsoft Dynamics, or enterprise data integration architectures.
Experience with Azure, Databricks, Python, and SQL.
Experience with large-scale cloud data infrastructure, data lakes, or distributed data processing.
Familiarity with procurement, spend analytics, supply chain, or enterprise finance processes.
Experience working with customer finance, information security, or IT teams, external technology partners, or software vendors.
Culture & Benefits
Flexible hybrid work with a Helsinki office and tools for remote work.
Freedom and responsibility, with trust to own work and make decisions.
International workforce representing more than 40 nationalities.
Equity program, extensive healthcare, phone plan, home internet connection, referral bonus, sports and culture benefits, and self-development support.
Family-friendly environment and opportunities to participate in office and team events.
Hiring process
Submit a CV and optionally a few words about strengths and motivation for leading the Connectors & Data Factory team.
Interviews include conversations with a Talent Acquisition Partner, the future manager, Engineering Managers, and the SVP of Engineering.
The process includes a technical system-thinking conversation with engineers, without a coding exercise; expectations are shared before each stage.
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