Presales Solutions Architect - Data & AI

Unisys; Bengaluru; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

Unisys is seeking an experienced Presales Architect - Applications to design scalable, secure data architectures for enterprise environments. The role focuses on EDW/ODS data integration, data governance, and modernization initiatives, partnering with sales and delivery teams to win complex engagements.

You will lead architecture design, cost modeling, and technical proposal development, leveraging GenAI tools to accelerate documentation and ensure alignment with business value.

Qualifications

• BA/BS degree required with 10+ years of relevant experience or equivalent
• Master’s degree preferred for advanced data architecture
• Proven track record in presales, data architecture design, and large-scale data solutions

Responsibilities

• Lead discovery to assess enterprise data ecosystems and legacy platforms
• Design end-to-end data architectures including EDW, ODS, data marts, and reporting
• Develop cost models covering hardware, software, and operations with ROI analysis
• Create technical proposals with data architectures, roadmaps, and migration plans
• Define data governance, security, and metadata management frameworks
• Collaborate with sales, delivery, and finance to ensure proposal feasibility and value

Skills

Enterprise data architecture

On-premises data platforms

Cost modeling

Technical proposal development

GenAI tooling

Education

BA/BS degree

Master’s degree preferred

Tools

ETL tools

BI tools

GenAI tools

Job description

What success looks like in this role: We are seeking an experienced Presales Architect - Applications with deep expertise in enterprise data architecture and on-premises data platforms to support complex sales engagements. This role focuses on designing scalable, secure, and high-performance data solutions within traditional enterprise environments, enabling organizations to modernize legacy systems, improve data governance, and enhance analytics capabilities. You will partner with sales, delivery, and customer stakeholders to shape data strategies, build compelling proposals, and deliver measurable business outcomes.

• Key Responsibilities 1. Solution Architecture & Design Lead discovery sessions to assess existing enterprise data ecosystems, legacy platforms, and business requirements Design end-to-end data architectures including: Enterprise Data Warehouses (EDW) Operational Data Stores (ODS) Data marts and reporting systems Batch and near real-time data integration Define architectures across: Relational databases (Oracle, SQL Server, DB2, Teradata, etc.) ETL and data integration tools Storage, archival, and lifecycle management systems Develop logical and physical data models aligned to business needs Ensure architectures meet requirements for performance, scalability, high availability, and disaster recovery Present solutions to technical and business stakeholders, linking architecture to business value
• Key Responsibilities 2. Cost Modeling & Financial Analysis Develop detailed cost models covering: Hardware (servers, storage, networking) Software licensing (databases, ETL, BI tools) Data processing and integration workloads Ongoing operations and support Build bottom-up estimates using: Data volumes and growth projections Workload and performance requirements Conduct ROI and TCO analysis for: Legacy modernization initiatives Platform consolidation and optimization Compare alternative architecture approaches (e.g., centralized vs distributed data platforms) Validate cost assumptions with delivery and finance teams
• Key Responsibilities 3. Technical Proposal Development Develop comprehensive proposals including: Data architecture diagrams Data flow and integration patterns Implementation roadmaps and migration plans Resource planning and timelines Risk mitigation strategies and governance models Clearly articulate business value including: Improved data quality and reliability Faster reporting and analytics Operational efficiency and cost savings Collaborate with delivery, engineering, and finance teams to ensure feasibility Use GenAI tools (e.g., Microsoft Copilot, ChatGPT) to: Accelerate documentation Improve clarity and structure of proposals Synthesize complex requirements
• Key Responsibilities 4. Data Modernization & Transformation Define strategies for: Legacy data warehouse modernization Data platform consolidation ETL optimization and re-engineering Data archival and lifecycle management Recommend approaches such as: Replatforming to modern database systems Data model redesign (dimensional, normalized, data vault) Enable capabilities for: Near real-time data availability Improved reporting performance Better data accessibility
• Key Responsibilities 5. Data Governance, Quality & Security Design and implement frameworks for: Data governance and stewardship Data quality management Metadata management and lineage Ensure compliance with enterprise security standards: Role-based access control Data masking and encryption Regulatory compliance requirements
• Key Responsibilities 6. Delivery Partnership & Post-Sales Alignment Ensure solutions are aligned with delivery capabilities and operational models Develop transition documents and implementation playbooks Support project kickoffs and early delivery alignment Define SLAs, KPIs, and operational metrics Capture feedback to improve solution quality and reusability

You will be successful in this role if you have: BA/BS degree and 10+ years’ relevant experience OR equivalent combination of education and experience Master’s degree preferred. Experience 8–12 years of experience in data architecture, data engineering, or presales consulting Minimum 5 years focused on enterprise data platforms in on-premises environments Proven track record in: Designing enterprise data solutions Supporting and influencing large deals Building cost models and ROI justifications Experience in RFP responses and technical proposal development