Data Delivery Manager (AI / Data Platforms)
EPAM · зарплата не указана · локация не указана · сайт компании · опубликовано 5 июня 2026 г.
Описание вакансии
We are seeking an experienced Data Delivery Manager to lead large-scale Data & AI initiatives, including advanced Generative AI and Machine Learning solutions. This role demands a leader with strong delivery discipline, deep knowledge of data ecosystems, and the capability to drive transformation programs across business and technology teams.
You will play a key role in directing high-impact AI and data initiatives, working closely with senior stakeholders and expert engineering teams to implement scalable solutions that influence business results.
Responsibilities
Lead end-to-end delivery of complex Data & AI programs, from strategy and architecture definition to production deployment
Collaborate with senior business stakeholders, data scientists, and engineering teams to define scalable data and AI solutions
Deliver modern data platforms, including data pipelines, analytics capabilities, and AI/ML solutions in cloud environments
Establish delivery governance, execution frameworks, and KPIs to ensure predictable high-quality outcomes
Manage cross-functional teams and vendors to align stakeholders toward unified objectives
Ensure compliance with data governance, security, and regulatory standards within AI-driven environments
Identify delivery risks and implement proactive mitigation strategies in complex, dynamic environments
Requirements
Background in delivering large-scale Data Analytics / Data Science / AI initiatives
Understanding of data platforms, data engineering, and modern analytics ecosystems
Awareness of machine learning and generative AI concepts and their enterprise applications
Familiarity with public cloud platforms, data platform modernization, or cloud migration programs
Ability to navigate complex delivery landscapes involving diverse teams, technologies, and stakeholders
Leadership presence with communication abilities tailored to technical teams and executive stakeholders
Background in building and operating within AI SDLC frameworks such as agentic workflows and autonomous agents
Proficiency in Agile or hybrid delivery environments