Presales Solutions Architect - Data and Artificial Intelligence

Unisys India Private Limited; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Unisys India Private Limited is seeking a Senior Presales Solutions Architect - Data & AI to lead data architecture engagements for enterprise customers in Bengaluru. You will design scalable, secure data solutions, develop proposals, and quantify business value.

You will collaborate with sales, delivery, and finance teams to create compelling solutions, perform ROI analyses, and enable modernization of legacy systems while ensuring performance and governance.

Qualifications

• 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.
• Technical Expertise: Strong experience with enterprise database platforms: Oracle, SQL Server, DB2, Teradata, or similar.
• Deep understanding of: Data warehousing concepts (EDW, ODS, data marts), Data modeling techniques (dimensional, normalized, data vault).
• Hands-on experience with: ETL/ELT tools (Informatica, DataStage, SSIS, etc.).
• Batch and near real-time data integration.
• Knowledge of: Data governance, metadata, and data quality tools.
• BI tools: Power BI, Tableau, Cognos.
• GenAI tools for presales productivity and documentation.

Responsibilities

• Lead discovery sessions to assess existing enterprise data ecosystems, legacy platforms, and business requirements.
• Design end-to-end data architectures including: EDW, ODS, data marts and reporting systems.
• Define architectures across relational databases and ETL data integration tools.
• Develop cost models covering hardware, software licensing, and data processing workloads.
• Create technical proposals with data architecture diagrams, data flow, roadmaps, and timelines.
• Collaborate with delivery, engineering, and finance teams to ensure feasibility and governance.
• Leverage GenAI tools to accelerate documentation and improve clarity of proposals.

Skills

Data architecture

Presales experience

Enterprise data platforms

Cost modeling

ROI analysis

GenAI tooling

Communication skills

Team collaboration

Financial acumen

Education

BA/BS degree

Master's degree preferred

Tools

Informatica

DataStage

SSIS

Oracle

SQL Server

Teradata

Power BI

Tableau

Job description

Presales Solutions Architect - Data & AI

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 & DesignLead 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
2. Cost Modeling & Financial AnalysisDevelop 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
3. Technical Proposal DevelopmentDevelop 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
4. Data Modernization & TransformationDefine 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
5. Data Governance, Quality & SecurityDesign 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
6. Delivery Partnership & Post-Sales AlignmentEnsure 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
• Technical Expertise Strong experience with enterprise database platforms: Oracle, SQL Server, DB2, Teradata, or similar Deep understanding of: Data warehousing concepts (EDW, ODS, data marts) Data modeling techniques (dimensional, normalized, data vault) Hands-on experience with: ETL/ELT tools (Informatica, DataStage, SSIS, etc.) Batch and near real-time data integration Knowledge of: Data governance, metadata, and data quality tools Performance tuning and query optimization Experience with: High availability, backup, and disaster recovery strategies Familiarity with BI/reporting tools (Power BI, Tableau, Cognos, etc.)
• Proficiency in using GenAI tools for presales productivity and documentation Business & Soft Skills Strong ability to translate data architecture into business value Excellent communication and presentation skills Consultative approach to discovery and problem-solving Ability to manage multiple presales opportunities Strong collaboration across cross-functional teams Financial acumen in cost modeling and ROI analysis

Certifications & Nice-to-Haves

• Certifications in database technologies or data management Knowledge of frameworks such as DAMA-DMBOK Experience in system integrators or managed services environments Familiarity with MPP or appliance-based data systems (e.g., Teradata, Netezza) Experience with data modeling tools (ERwin, ER/Studio, etc.) Thought leadership in enterprise data architecture

Success Metrics

• Contribution to deal wins involving data solutions Accuracy and competitiveness of cost models Quality and scalability of architecture designs Customer satisfaction and successful delivery alignment Reusability of solution frameworks and assets

Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, blood type, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law. Local employment practices and rights may vary by jurisdiction and are subject to applicable local laws. This commitment includes our efforts to provide for all those who seek to express interest in employment the opportunity to participate without barriers.

If you are a US job seeker unable to review the job opportunities herein, or cannot otherwise complete your expression of interest, without additional assistance and would like to discuss a request for reasonable accommodation, please contact our Global Recruiting organization at [e-mail] . US job seekers can find more information about Unisys’ EEO commitment here .

Experience Level

Senior Level

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