Senior Data Delivery Manager (Engagement Lead)
Join us as a Senior 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
- 8+ 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
