Data Delivery Manager (Engagement Lead)

Join us as a Data Delivery Manager and become the trusted Engagement Lead for enterprise-scale data and AI programs. You’ll steer engagements that modernize data estates, activate analytics, and embed AI — from the first strategic conversation through delivery and continuous value realization. Acting as the connective tissue between Sales, Delivery, Solution Architects, and client stakeholders, you’ll ensure data-led commitments translate into measurable outcomes and long-term partnerships.

Responsibilities

• 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 to 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 best practices
• Validate SOWs and commercials to ensure feasibility, profitability, and alignment with client data goals
• Coordinate multiple delivery streams across data engineers, data scientists, analytics specialists, data architects, product owners, and fellow Delivery Managers — supporting both mature data organizations and greenfield team buildouts. Outcome: High-performing, data-focused delivery teams operating within governance models you design and continuously refine
• Establish and run delivery governance with data-centric KPIs, risk frameworks, quality gates, and escalation paths — leveraging best practices across modern cloud and analytics ecosystems
• Spot and cultivate growth opportunities by recommending data capability roadmaps, platform optimizations, and AI/analytics extensions
• Contribute to account strategy and presales, mentor junior Delivery Managers, and foster a consultative, data-first culture focused on business outcomes

Requirements

• 5+ years of experience in IT services, consulting, or digital delivery with a sustained focus on data platforms, analytics, AI/ML, data migration, or data governance programs
• Proven ability to lead multi-stream data engagements for enterprise clients, orchestrating cross-functional and globally distributed teams
• Demonstrated success in data-focused presales and solution shaping, aligning business value, data strategy, and delivery economics
• Excellent stakeholder management, communication, negotiation, and escalation skills in English (B2+ required); additional languages are a plus
• Systems-thinking mindset with the ability to connect sales, delivery, operations, and data value realization
• Strong understanding of data architecture patterns, governance, quality, privacy/compliance, and how they translate into delivery plans and operating models
• Experience translating data strategy into actionable roadmaps, KPIs, and execution plans while balancing stakeholder priorities
• Working knowledge of modern data platforms and toolchains (e.g., Azure/AWS/GCP analytics services, Databricks, Snowflake, Power BI/Tableau, dbt, MLOps practices) — sufficient to challenge assumptions, guide conversations, and support technical teams