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Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Это хорошо очерченная руководящая роль с заметной ответственностью за платформу данных для аналитики и ИИ, хотя конкретные инструменты и условия работы раскрыты не полностью.
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Manager, Data Platform Engineering (AI): Building and operating governed data lake/lakehouse capabilities, pipelines, integrations, and data models for enterprise analytics, AI, and digital transformation with an accent on scalability, security, reliability, and data governance. Focus on establishing engineering standards, integrating enterprise systems, managing platform resources, and transitioning critical pipelines into monitored DataOps operations.
Company
hirify.global develops solutions for the biopharmaceutical and clinical markets, with a focus on innovation, customer centricity, collaboration, sustainability, and employee engagement.
What you will do
Lead the design and delivery of the next-generation enterprise data platform, including data lake/lakehouse structures, pipelines, integrations, and central data models.
Establish engineering standards for ingestion, transformation, CI/CD, version control, documentation, testing, observability, and environment management.
Manage data platform engineering resources and external consultants supporting platform buildout.
Partner with analytics, data science, AI engineering, IT, cybersecurity, governance, and business stakeholders to prioritize data products and integrations.
Ensure pipelines and data products are reliable, secure, scalable, documented, and aligned with governance and quality expectations.
Coordinate the integration of enterprise systems and priority data sources, and transition critical pipelines into monitored, supportable DataOps operations.
Requirements
Bachelor’s degree in computer science, data engineering, information systems, engineering, or a related field.
Experience leading data engineering, data architecture, cloud data platform, or enterprise integration work.
Strong understanding of data lakes/lakehouses, pipelines, data modeling, CI/CD, orchestration, APIs, version control, and data quality practices.
Experience managing technical teams, consultants, or vendors.
Familiarity with enterprise applications, governed analytics environments, and secure data access patterns.
Strong collaboration skills across IT, business, analytics, and AI stakeholders.
Nice to have
Experience with Microsoft Fabric, Azure, Databricks, SAP, Salesforce, or modern data governance tools.
Experience building platform operating models, data product practices, or DataOps handoff processes.
Experience in medical device, diagnostics, life sciences, manufacturing, or regulated environments.
Culture & Benefits
Culture focused on transparency, sustainability, effective communication, collaboration, and employee engagement.
Opportunities for professional growth and development.
Full-time employees can generally expect health coverage, retirement savings options, paid time off, wellness initiatives, and development resources.
Benefits vary by country and employment type.
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