Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this SAP Managing Analytics Architect role.

Rezi rewrites your resume against Capgemini's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the SAP Managing Analytics Architect posting at Capgemini — free, in seconds.

About the Role

As a Managing Analytics Architect within Capgemini's SAP Data & Analytics Practice, you will provide strategic leadership and architectural governance across complex analytics and data transformation programmes. You will partner with C-suite stakeholders to define and execute strategic data and analytics roadmaps, shaping enterprise-wide SAP analytics strategies across major SAP S/4HANA transformation programmes. You will also contribute to solution development, client account growth, and capability building within Capgemini.

Responsibilities

Lead the end-to-end architecture and design of enterprise SAP analytics and data platforms.
Define analytics strategies aligned to broader SAP S/4HANA business transformation programmes.
Act as a trusted advisor to CIOs, CDOs, CFOs and business executives on data and analytics strategy.
Design target-state SAP Business Data Cloud, SAP Datasphere and SAP Analytics Cloud architectures.
Establish enterprise reporting, data governance and semantic modelling frameworks.
Lead analytics assessments, maturity reviews and transformation roadmaps.
Define data products, business semantic layers and enterprise information models.
Provide architectural oversight across multiple delivery workstreams and transformation programmes.
Advise clients on the migration of SAP BW and BW/4HANA landscapes to SAP's strategic cloud data architecture.
Develop analytics operating models, governance structures and best-practice frameworks.
Collaborate with AI, Data, Cloud and Enterprise Architecture teams to create integrated business solutions.
Lead architecture workshops, executive presentations and steering committee engagements.
Support pre-sales activities, business development and major proposal responses.
Mentor and develop consulting teams, architects and technical specialists.
Identify opportunities for innovation through AI, automation and data-driven decision intelligence.

Requirements

Extensive experience delivering enterprise-scale SAP Analytics and Data Transformation programmes.
Proven experience leading analytics architecture engagements for complex organisations.
Deep expertise across SAP Analytics Cloud, SAP Datasphere and SAP Business Data Cloud.
Strong understanding of SAP S/4HANA Embedded Analytics and operational reporting frameworks.
Expertise in enterprise data architecture, information management and analytics strategy.
Strong understanding of SAP BW, BW on HANA and BW/4HANA architectures.
Experience designing modern Business Data Fabric and cloud-based analytics solutions.
Strong knowledge of data governance, data quality and metadata management frameworks.
Experience developing executive-level analytics and data transformation strategies.
Ability to engage credibly with Executive Committees, Boards and senior business stakeholders.
Strong consulting, stakeholder management and communication skills.
Experience leading multi-disciplinary teams and large-scale transformation programmes.
Strong understanding of enterprise architecture methodologies and governance models.
Experience operating within complex matrix organisations and consulting environments.
Experience leading SAP Business Data Cloud transformation initiatives.
Knowledge of SAP AI, Joule and Business AI capabilities.
Experience with SAP Data Intelligence and SAP Integration Suite.
Understanding of Master Data Management and SAP Master Data Governance (MDG).
Experience with Microsoft Azure, AWS or Google Cloud data platforms.
Experience with Data Mesh and Data Product operating models.
Knowledge of AI, Machine Learning and Advanced Analytics architectures.
SAP Activate methodology experience.
TOGAF, SAFe or equivalent architecture certifications.
SAP Analytics Cloud, Datasphere or Business Data Cloud certifications.
Experience supporting clients within Financial Services, Public Sector, Utilities, Manufacturing or Consumer Products sectors.
Experience leading global delivery and offshore engagement models.

Skills

SAP Analytics Cloud
SAP Datasphere
SAP Business Data Cloud
SAP S/4HANA Embedded Analytics
SAP BW
BW on HANA
BW/4HANA
Business Data Fabric
Cloud-based analytics
Data governance
Data quality
Metadata management
AI
Automation
Data-driven decision intelligence
SAP AI
Joule
Business AI
SAP Data Intelligence
SAP Integration Suite
Master Data Management
SAP Master Data Governance (MDG)
Microsoft Azure
AWS
Google Cloud data platforms
Data Mesh
Data Product operating models
Machine Learning
Advanced Analytics architectures
SAP Activate methodology
TOGAF
SAFe

Location

Work Type

Hybrid Working
Home working
Office collaboration
Client-site attendance
Flexible working arrangements

Experience Level

Senior leader
Managing

Education Level

TOGAF, SAFe or equivalent architecture certifications
SAP Analytics Cloud, Datasphere or Business Data Cloud certifications

Benefits

Encouraged positive work-life balance
Countless training and development opportunities
Access to 250,000 courses
External certifications from AWS, Microsoft, Harvard Manage Mentor, Cybersecurity qualifications

About the Company

Capgemini's SAP Data & Analytics Practice is a market-leading team delivering complex business transformation programmes across the UK and globally.
At Capgemini, we help organisations across the world become more agile, more competitive, and more successful.
Smart, tailored, often ground-breaking technical solutions to complex problems are the norm.
Capgemini fosters a culture that’s as collaborative as it is forward thinking.
Capgemini represents nearly 130 nationalities and its cultural diversity.
Capgemini values diversity of thought, encompassing gender, gender identity, sexual orientation, disability, ethnicity, race, age, religion, social background, life and work experiences, communication styles and personality.