Insights & Data (I&D) Advisory Lead -Proactive at Capgemini
London, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

16 Sep, 25

Salary

0.0

Posted On

17 Jun, 25

Experience

8 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

GET THE FUTURE YOU WANT!

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

Responsibilities

We are looking for a highly skilled and strategic Senior Data Advisory Lead with deep expertise in financial services to join the Insights and Data (I&D) FS practice.

This role is ideal for a data leader who thrives at the intersection of business strategy, data innovation, and regulatory compliance. You will work with Tier 1 banks, to design and implement data strategies that drive transformation, mitigate risk, and unlock business value.

  • Act as a trusted advisor to senior executives (CDOs, CIOs, CROs, CFOs) on data-driven transformation.
  • Lead cross-functional teams to deliver complex enterprise data initiatives and transformation programs.
  • Conduct executive workshops, board-level presentations, and strategic briefings to align stakeholders.
  • Craft and deliver persuasive pitches to senior leadership to secure buy-in for data initiatives.
  • Design and execute data-driven pricing strategies to enhance revenue and profitability.
  • Develop enterprise-wide data strategies aligned with business objectives and compliance mandates.
  • Conduct maturity assessments and gap analyses across data governance, architecture, and analytics.
  • Define and implement data operating models, target architectures, and transformation roadmaps.
  • Establish data governance frameworks (e.g., DAMA, DCAM) and define stewardship roles and KPIs.
  • Support deployment of metadata management, data lineage, and cataloging tools across platforms.
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