Pre-Sales Solution Architect
Fujitsu
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Benefits offered by this job
Job summary
Fujitsu is seeking a Pre-Sales Solution Architect for Data Services and Analytics to shape and position data-led transformation for global customers.
You will collaborate with Sales, Industry Leads, Delivery Teams, and Partners to define solutions, respond to RFPs, and articulate business value of Data AI platforms.
Qualifications
- 10+ years of experience in Data Services, Data Engineering, Analytics, Data Integration, or Data Architecture.
- 5+ years in customer-facing consulting, pre-sales, solutioning, or architecture roles.
- Proven experience shaping and winning large-scale Data Analytics transformation engagements.
Responsibilities
- Engage with region/customers to understand objectives, data maturity, and transformation priorities.
- Lead discovery workshops and discussions with business and tech stakeholders.
- Identify opportunities for Data Modernization, Analytics Transformation, and Data Governance.
Skills
Tools
Job description
The Pre-Sales Solution Architect for Data AI is a strategic and customer-facing role within the Global Pre-Sales Solutions (GPS) organization responsible for shaping, designing, and positioning business-led Data, Analytics, AI/ML, DataOps, and Cloud Data Platform solutions for global customers.
The role works closely with Sales, Industry Leads, Delivery Teams, UVANCE Digital Shifts, Technology Partners, and Global Solution Architects to qualify opportunities, define solution, design delivery roadmaps, respond to RFPs, create differentiated solutions, and articulate the business value of Data AI-led transformation.
- Engage with region / customers to understand business objectives, challenges, data maturity, and transformation priorities.
- Lead discovery workshops, assessments, and discussions across business and technology stakeholders.
- Identify opportunities for Data Modernization, Data Migration, Analytics Transformation, AI Enablement, Data Governance, and Managed Services.
- Design end-to-end Data AI solutions encompassing:
- Data Platforms
- Modern Data Warehouses
- Data Lakes and Lakehouse Architectures
- Data Integration Engineering
- Business Intelligence Analytics
- AI/ML Platforms
- Data Governance Data Quality
- DataOps MLOps
- Define target-state architectures, operating models, roadmaps, and implementation approaches.
- Create scalable, secure, resilient, and cost-effective cloud-native architectures.
- Lead solution development for RFPs, RFIs, proposals, and customer presentations.
- Develop solution narratives, effort estimations, assumptions, risks, and transition strategies.
- Collaborate with delivery teams to create commercially viable and technically feasible solutions.
- Contribute to pricing models, resource plans, and service definitions.
- Data Lakes
- Data Warehouse
- Lakehouse Architectures
- Enterprise Data Platforms
- Data Mesh
- Data Fabric
- Data Integration
- ETL / ELT Design
- Data Modelling
- Master Data Management
- Enterprise Reporting
- Self-Service Analytics
- Operational Intelligence
- Dashboard Strategy
- KPI Frameworks
- Data Storytelling
- Machine Learning Lifecycle
- Predictive Analytics
- Data Science
- MLOps
- AI Governance
- Responsible AI
- Generative AI
- AI Agents
- Cognitive Services
- CI/CD for Data Pipelines
- Data Observability
- Data Reliability Engineering
- Pipeline Automation
- DevSecOps Integration
- Monitoring Continuous Improvement
- Azure Data Factory
- Azure Synapse
- Azure Databricks
- Azure Data Lake
- Microsoft Fabric
- Azure Machine Learning
- Azure Purview
- AWS Glue
- Redshift
- S3
- BigQuery
- Dataflow
- Vertex AI
- Snowflake
- Databricks
- Cloudera
- Palantir
- Talend
- Win Rate
- AI Data Services Solutions Quality in deals
- Competitive Pricing
- Team Player
- Customer Satisfaction
- 10+ years of experience in Data Services, Data Engineering, Analytics, Data Integration, Data Platforms, or Data Architecture.
- 5+ years in customer-facing consulting, pre-sales, solutioning, or architecture roles.
- Proven experience shaping and winning large-scale Data Analytics transformation engagements.
- Experience designing enterprise-wide Data Platforms and Data Modernization programs.
- Experience developing business cases, proposals, and strategic transformation roadmaps.
Experience across enterprise data strategy, governance, AI adoption roadmaps, generative AI use cases, data monetization, self-service analytics, and data product operating models.
- Data quality, metadata management, lineage, compliance, regulatory controls, and information security.
- Ability to position DataOps, AIOps, automation, and managed services for continuous improvement.
- Partner with regional sales, service lines, partner ecosystems, and delivery teams to shape differentiated solutions.
- Contribute to deal assurance, pursuit strategy, governance, and solution quality improvement.
Relocation Supported: Yes
Visa Sponsorship Approved: No
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