Presales Solutions Architect - Data & AI

Overview

Design enterprise data architectures and support complex presales engagements involving on-premises data platforms. Partner with sales, delivery, and customer stakeholders to shape data strategies, develop proposals, and deliver measurable business outcomes.

What you'll do

• Lead discovery sessions to assess enterprise data ecosystems, legacy platforms, and business requirements.
• Design end-to-end data architectures for enterprise data warehouses, operational data stores, data marts, reporting systems, and batch and near real-time data integration.
• Define architectures across relational databases, ETL and data integration tools, and 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.
• Develop cost models covering hardware, software licensing, data processing and integration workloads, and ongoing operations and support.
• Build bottom-up estimates using data volumes, growth projections, workload requirements, and performance requirements.
• Conduct ROI and TCO analysis for legacy modernization, platform consolidation, and optimization initiatives.
• Compare alternative architecture approaches and validate cost assumptions with delivery and finance teams.
• Develop technical proposals containing architecture diagrams, data flows, implementation roadmaps, migration plans, resource planning, timelines, risk mitigation strategies, and governance models.
• Use GenAI tools such as Microsoft Copilot and ChatGPT to accelerate documentation, improve proposal clarity and structure, and synthesize complex requirements.
• Define strategies for legacy data warehouse modernization, data platform consolidation, ETL optimization and re-engineering, and data archival and lifecycle management.
• Recommend replatforming, data model redesign, and approaches that enable near real-time data availability, improved reporting performance, and better data accessibility.
• Design and implement data governance, stewardship, data quality, metadata, and lineage frameworks.
• Ensure compliance with enterprise security standards, including role-based access control, data masking and encryption, and regulatory compliance requirements.
• Align solutions 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, and capture feedback to improve solution quality and reusability.

What you'll need

• BA/BS degree and 10+ years’ relevant experience, or an equivalent combination of education and 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 designing enterprise data solutions, supporting and influencing large deals, and building cost models and ROI justifications.
• Experience in RFP responses and technical proposal development.
• Strong experience with enterprise database platforms including Oracle, SQL Server, DB2, Teradata, or similar.
• Deep understanding of data warehousing concepts, including EDW, ODS, and data marts.
• Deep understanding of dimensional, normalized, and data vault data modeling techniques.
• Hands-on experience with ETL/ELT tools such as Informatica, DataStage, and SSIS.
• Hands-on experience with batch and near real-time data integration.
• Knowledge of data governance, metadata, and data quality tools.
• Knowledge of performance tuning and query optimization.
• Experience with high availability, backup, and disaster recovery strategies.
• Familiarity with BI/reporting tools such as Power BI, Tableau, and Cognos.
• Proficiency in using GenAI tools for presales productivity and documentation.
• 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.

Nice to have

• Master’s degree.
• 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 such as Teradata and Netezza.
• Experience with data modeling tools such as ERwin and ER/Studio.
• Thought leadership in enterprise data architecture.

Details

• Location: Bangalore - RGA Tech Park.