Data Delivery Head for Serbia

Responsibilities

• Act as the local leadership for the data practice in Serbia, owning organizational design, structure, and growth of the local data delivery team as the practice scales, alongside full P&L responsibility for the Serbia data unit (utilization, margin, and cost management)
• Drive talent management and hiring for the local data organization — performance management, retention, succession planning, and skill development — partnering with Talent Acquisition to build pipeline for key data engineering, analytics, and architecture roles
• Own end-to-end data engagements — from opportunity qualification and innovation workshops, through solution shaping, delivery, stabilization, and account expansion. Outcome: Data programs delivered on time, within budget, and aligned to agreed business outcomes
• Become a strategic data advisor to executive sponsors, business owners, IT leaders, and Chief Data/Analytics Officers across our global enterprise client base (Europe, the Americas, LATAM, APAC). Outcome: Expansion of client relationships through new or extended data & AI initiatives that you help identify and shape
• Lead client communication and governance: set cadence, run steering committees, negotiate scope, manage expectations, and resolve escalations. Outcome: Recognition as a trusted data advisor, with your recommendations driving a measurable impact on client strategies and platforms
• Drive business value in initiatives such as data platform and Lakehouse buildouts, enterprise data warehouse modernization, cross-platform data migrations, advanced analytics, ML/AI activation, and data governance transformations
• Frame target-state data visions with clients — connecting business priorities to data strategy, operating models, KPIs, and transformation roadmaps
• Partner with Sales and Solution Architects during presales to shape delivery models, define data capabilities, and architect scalable approaches for complex data ecosystems
• Ensure seamless deal-to-delivery transitions, clarifying scope, governance, team structure, and execution plans grounded in data operating model best practices
• Validate SOWs and commercials to ensure feasibility, profitability, and alignment with client data goals

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