Pre-Sales Solution Architect

Fujitsu Careers; Pune District; Hybrid; INR 3,500,000 - 7,500,000; Full time

Job summary

Fujitsu is seeking a Pre-Sales Solution Architect for Data & AI to shape, design, and position business-led data, analytics, AI/ML, and cloud data platform solutions for global customers. You will work with Sales, Industry Leads, and Delivery teams to qualify opportunities and craft differentiated solutions.

You will define target architectures, respond to RFPs, and articulate business value across Data Lakes, Data Warehouses, Lakehouse architectures, and AI governance.

Qualifications

• 10+ years in Data Services, Data Engineering, Analytics, 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

• Qualify opportunities and design data & AI solutions for global customers.
• Lead discovery workshops with business and technical stakeholders.
• Define target-state architectures, roadmaps, and delivery approaches.
• Respond to RFPs and create solution narratives and estimates.
• Collaborate with delivery teams to ensure commercially viable solutions.

Skills

Data platforms

Data lakes

Data warehouse

Lakehouse architectures

Data governance

AI/ML platforms

MLOps

Data integration

Cloud data platforms

Business storytelling

Tools

Azure ML

AWS SageMaker

Databricks

Palantir

TensorFlow

Scikit-learn

Job description

Location Flexibility: Multiple Locations in Country

Posting Start Date: 9/8/26

Role Summary

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.

Key Responsibilities

• Opportunity Qualification
• 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.
• Data Platforms
• Modern Data Warehouses
• Data Lakes and Lakehouse Architectures
• 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.
• RFP Response & Solution Development
• 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.

Core Technical Expertise

• Data Lakes
• Data Warehouse
• Lakehouse Architectures
• Data Mesh
• Data Fabric
• Data Integration
• ETL / ELT Design
• Master Data Management
• Self-Service Analytics
• Dashboard Strategy
• KPI Frameworks
• Data Storytelling

Artificial Intelligence & Machine Learning

• Machine Learning Lifecycle
• Predictive Analytics
• Data Science
• MLOps
• AI Governance
• Responsible AI
• Generative AI
• AI Agents
• Cognitive Services

Platforms and ecosystems include Azure ML, AWS SageMaker, Databricks, Palantir, TensorFlow and Scikit-learn capabilities reflected in current Fujitsu Data & AI solutions.

DataOps & MLOps

• CI/CD for Data Pipelines
• Data Observability
• Data Reliability Engineering
• DevSecOps Integration
• Microsoft Fabric

AWS

• AWS Glue
• Redshift
• S3

GCP

• BigQuery
• Dataflow

Modern Data Platforms

• Snowflake
• Databricks
• Cloudera
• Palantir
• Talend

Success Metrics

• Win Rate
• AI & Data Services Solutions Quality in deals
• Team Player
• Customer Satisfaction

Required Experience

• 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.

Preferred Skills & Advisory Experience

Experience across enterprise data strategy, governance, AI adoption roadmaps, generative AI use cases, data monetization, self-service analytics, and data product operating models.

Good to Have Skills

• Data quality, metadata management, lineage, compliance, regulatory controls, and information security.
• Ability to position DataOps, AIOps, automation, and managed services for continuous improvement.

Collaboration & Stakeholder Management

• 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.