Managing Director, Enterprise Data Platform

Build and maintain trusted relationships with C-suite executives, business leaders, and senior technology stakeholders.

Advise clients on enterprise data strategy, platform architecture, technology selection, operating models, investment priorities, and transformation roadmaps.

Manage and grow a book of business spanning multiple clients and engagements.

Originate new opportunities and expand existing client relationships by identifying additional needs and developing relevant solutions.

Lead business-development activities, including opportunity qualification, solution development, proposal preparation, pricing, presentations, and contract negotiations.

Communicate the business value of enterprise data platforms and connect technical investments to measurable financial and operational outcomes.

Represent Ankura’s Digital Transformation practice in the market through executive relationships, industry forums, strategic partnerships, and thought leadership.

Provide executive sponsorship and delivery oversight across a portfolio of complex data-platform programs.

Ensure engagements are appropriately scoped, staffed, governed, and aligned with client objectives and contractual commitments.

Oversee large-scale data integration and platform implementations using technologies such as Databricks, Snowflake, Microsoft Fabric, and comparable platforms.

Guide data orchestration and integration strategies using technologies such as Azure Data Factory, Airflow, Informatica, and other enterprise tools.

Monitor engagement economics, delivery quality, resource utilization, risks, timelines, and client satisfaction.

Ensure platforms meet expectations for scalability, reliability, security, governance, performance, maintainability, and cost efficiency.

Intervene proactively to resolve significant technical, delivery, commercial, or client relationship issues.

Maintain accountability for high-quality delivery and measurable client outcomes across the portfolio.

Build, lead, and develop multidisciplinary teams of data architects, data engineers, data scientists, technical leads, and delivery professionals.

Recruit and retain high-performing professionals across onshore, nearshore, and offshore delivery teams.

Establish clear roles, career paths, competency expectations, and development plans for technical team members.

Mentor senior leaders and create opportunities for them to assume greater client, commercial, and delivery responsibility.

Promote collaboration among data engineering, data science, analytics, automation, AI, business transformation, and change-management professionals.

Develop scalable staffing and delivery models that support practice growth while maintaining quality and financial performance.

Typically 12–15+ years of experience in data engineering, enterprise data architecture, analytics, or related technology consulting, including substantial senior leadership responsibility.

Proven experience leading the design and delivery of enterprise-grade cloud data platforms and large-scale data transformation programs.

Demonstrated success managing and growing a significant book of consulting business across multiple clients.

Established record of developing executive client relationships, originating opportunities, and converting those opportunities into successful engagements.

Deep knowledge of enterprise data architecture, integration, data modeling, governance, metadata management, data quality, security, and cloud-platform principles.

Strong experience with data and analytics platforms such as Databricks, Snowflake, Microsoft Fabric, or comparable technologies.

Strong understanding of ETL, ELT, and orchestration technologies such as Azure Data Factory, Airflow, Informatica, or similar platforms.

Ability to connect data-platform investments to business strategy, operational improvement, financial performance, and measurable value realization.

Demonstrated experience overseeing multiple concurrent engagements, delivery teams, and client relationships.

Proven ability to recruit, organize, mentor, and develop high-performing technical and consulting teams.

Strong commercial judgment, including experience with engagement economics, pricing, contracting, resource planning, and risk management.

Executive-level communication, presentation, facilitation, and relationship-management skills.

Strong business acumen, entrepreneurial orientation, and results-focused leadership style.

leading geographically distributed, multi-team, or multi-vendor delivery models is strongly preferred.

with advanced analytics, machine learning, generative AI, real-time data processing, or AI-enabled enterprise solutions is preferred.

Relevant cloud, data-platform, or architecture certifications are beneficial.

Willingness to travel up to 20-25% including potential international travel.

Bachelor’s degree in computer science, engineering, information systems, data science, or a related field is required; an advanced degree is preferred.

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