Pre-Sales Solution Architect

Role Summary

The Pre-Sales Solution Architect for Data & AI is a customer-facing role responsible for shaping, designing, and positioning Data, Analytics, AI/ML, DataOps, and Cloud Data Platform solutions for global customers. The role works closely with Sales, Industry Leads, Delivery Teams, Technology Partners, and Global Solution Architects to qualify opportunities, develop solutions, respond to RFPs, and articulate the business value of Data & AI transformation.

Key Responsibilities

• Lead customer discovery, assessments, and solution workshops.
• Identify opportunities for Data Modernization, Data Migration, Analytics Transformation, AI Enablement, Data Governance, and Managed Services.
• Design end-to-end Data & AI solutions covering Data Platforms, Data Warehouses, Lakehouses, Data Integration, Analytics, AI/ML, Data Governance, DataOps, and MLOps.
• Develop target-state architectures, roadmaps, operating models, and implementation approaches.
• Lead solution development for RFPs, RFIs, proposals, and customer presentations.
• Create solution narratives, estimations, assumptions, risks, and transition strategies.
• Collaborate with delivery teams to develop commercially viable and technically feasible solutions.
• Support pricing models, resource plans, and service definitions.

Technical Expertise

Data Platforms & Engineering

• Data Lakes, Data Warehouses, Lakehouse Architectures
• Enterprise Data Platforms, Data Mesh, Data Fabric
• Data Integration, ETL/ELT
• Data Modelling and Master Data Management

Analytics & BI

• Enterprise Reporting
• Self-Service Analytics
• Operational Intelligence
• Dashboard Strategy
• KPI Frameworks
• Data Storytelling

AI/ML

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

DataOps & MLOps

• CI/CD for Data Pipelines
• Data Observability
• Pipeline Automation
• DevSecOps Integration
• Monitoring and Continuous Improvement

Cloud & Data Platforms

Microsoft Azure: Azure Data Factory, Synapse, Databricks, Data Lake, Microsoft Fabric, Azure ML, Purview

AWS: Glue, Redshift, S3

GCP: BigQuery, Dataflow, Vertex AI

Modern Data Platforms: Snowflake, Databricks, Cloudera, Palantir, Talend

Success Metrics

• Win Rate
• AI & Data Services Solution Quality
• Competitive Pricing
• Team Collaboration
• Customer Satisfaction