Senior Presales Solution Architect – Data Management, Analytics & AI/ML

Edgematics; India; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Edgematics in India is seeking an experienced Senior Presales Solution Architect – Data Management, Analytics & AI/ML to design enterprise data and analytics solutions and lead presales engagements.

You will work with customers, sales teams, partners and delivery teams to translate requirements into scalable, commercially viable architectures, spanning data engineering, governance, lakehouse, and AI platforms.

Qualifications

• 10+ years of experience in data, analytics, AI/ML or related fields.
• Proven presales, solution architecture or technical consulting background.
• Experience handling enterprise RFP/RFI responses.
• Strong understanding of modern data architectures (data lakehouse, MDM, governance).
• Experience with cloud platforms (Azure, AWS, GCP) and GenAI concepts.

Responsibilities

• Lead technical presales engagements for Data Management, Analytics and AI/ML.
• Translate customer requirements into practical solution architectures and proposals.
• Develop architecture artifacts and RFP responses with cross-functional teams.
• Collaborate with CIO/CDO/CTO leaders and data teams to align with business goals.
• Support sizing, estimation, and commercial aspects of opportunities.

Skills

Data Management

Data Engineering

Analytics

AI/ML

Presales

Solution Architecture

Education

Bachelor's or Master's in CS/IT

Job description

About Edgematics Edgematics is a global data and AI consulting company empowering Fortune 500 enterprises across the Middle East, Europe, the UK, North America, and India to unlock the true value of their data. Through our advanced platforms — PurpleCube AI (Data Orchestration & Analytics) and Axoma (Agentic AI) — we help organizations accelerate data modernization, governance, and AI adoption at scale. Our mission is to transform raw data into actionable intelligence through world-class engineering, innovation, and deep domain expertise.

Job Description

We are looking for an experienced Senior Presales Solution Architect – Data Management, Analytics & AI/ML with 10+ years of experience in designing enterprise data and analytics solutions and supporting complex presales engagements. The candidate will work closely with customers, sales teams, technology partners, delivery teams and internal SMEs to understand business and technical requirements and translate them into practical, scalable and commercially viable solution architectures and technical proposals. The role requires strong expertise across Data Engineering, Data Integration, Data Quality, Data Governance, MDM, Data Warehousing/Lakehouse, Cloud Data Platforms, BI & Analytics, AI/ML and Generative/Agentic AI, combined with strong customer-facing, proposal and solution-estimation capabilities.

Key Responsibilities :

Presales & Customer Engagement

• Lead technical presales engagements for Data Management, Analytics and AI/ML opportunities.
• Participate in customer discovery sessions, requirement workshops and technical discussions.
• Understand business objectives and translate them into technical requirements and solution capabilities.
• Identify gaps, assumptions, dependencies, risks and clarification points during opportunity qualification.
• Conduct technical presentations, solution walkthroughs and architecture discussions with customer stakeholders.
• Engage effectively with CIO/CDO/CTO organizations, enterprise architects, data teams and business stakeholders.
• Support sales teams throughout the opportunity lifecycle from qualification through proposal, technical evaluation and closure.

RFP / RFI / Proposal Management

• Analyze complex RFPs, RFIs, RFQs and Statements of Work.
• Extract functional, technical, infrastructure, security, integration, governance and non-functional requirements.
• Develop clarification questions and assumptions required for accurate solution design.
• Prepare comprehensive technical proposals and responses.
• Develop compliance matrices and requirement-to-solution mappings.
• Define solution scope, exclusions, assumptions, dependencies and customer responsibilities.
• Ensure technical proposals are aligned with customer requirements and evaluation criteria.
• Participate in technical defense sessions and proposal presentations.

Solution Architecture

• Design end-to-end enterprise architectures covering:
  • Data Integration and ETL/ELT
  • Batch and real-time data ingestion
  • CDC and data replication
  • Data Warehouses and Data Lakes
  • Modern Data Lakehouse architectures
  • Data Quality and Data Observability
  • Master Data Management
  • Metadata Management and Data Catalog
  • Data Governance
  • Data Lineage
  • API and application integration
  • Streaming and event-driven architectures
  • BI, Reporting and Self-Service Analytics
  • Semantic Layers
  • AI/ML and Generative AI platforms
  • Enterprise Agentic AI architectures
• Develop architecture artifacts including:
  • Conceptual Architecture
  • Logical Architecture
  • Physical / Deployment Architecture
  • Data Flow Architecture
  • Integration Architecture
  • Network Architecture
  • Security Architecture
  • HA/DR Architecture
  • DevSecOps / CI/CD Architecture
  • Data Governance Architecture
  • AI/ML and GenAI Architecture

Technology Evaluation & Solution Selection

• Evaluate and recommend technologies based on customer requirements, existing technology landscape, scalability, security, performance, cost and operational considerations.
• Expected exposure to technologies such as: Data Integration & Management, Data Platforms, Big Data & Streaming, Data Governance, Analytics.

• The candidate should be technology-agnostic and capable of selecting an appropriate technology stack rather than forcing a predefined product.

AI/ML, Generative AI & Agentic AI

• Support presales opportunities involving AI/ML and Generative AI.
• Design high-level enterprise AI/ML architectures covering data preparation, model development, deployment and monitoring.
• Understand LLM-based solution architectures, RAG, vector databases and enterprise knowledge architectures.
• Understand AI Agents and Agentic AI architectures.
• Define integration patterns between enterprise applications, data platforms, LLMs and AI services.
• Understand AI governance, model governance, responsible AI and security requirements.
• Define AI guardrails, model evaluation, observability and human-in-the-loop controls.
• Identify suitable AI/ML and GenAI use cases based on customer business requirements.
• Support AI/ML PoCs, prototypes and technical demonstrations.

Sizing, Estimation & Commercial Support

• Prepare implementation effort estimates and resource plans.
• Develop project timelines, work breakdown structures and delivery phases.
• Estimate person-days/person-months across project roles.
• Define resource loading and team composition.
• Develop phased implementation approaches including Discovery, PoC/Pilot, Implementation, UAT, Go-Live, Hypercare and Support.
• Support infrastructure sizing and Bill of Quantity (BoQ) preparation.
• Work with OEMs/technology partners for software licensing and infrastructure sizing.
• Support commercial teams in validating solution assumptions that influence pricing.

Infrastructure, Cloud & Non-Functional Design

• Understand on-premises, cloud and hybrid deployment architectures.
• Define infrastructure requirements for DEV/UAT/PROD and DR environments.
• Contribute to compute, storage and network sizing.
• Define HA/DR approaches including RPO/RTO considerations.
• Understand enterprise networking concepts including firewalls, load balancers, VPNs, proxies and DMZ architectures.
• Address security, encryption, IAM, RBAC, secrets management and audit requirements.
• Define monitoring, logging, backup and recovery requirements.

PoC & Technical Validation

• Define PoC objectives, scope and success criteria.
• Work with engineering teams to develop demonstrations and prototypes.
• Validate proposed technologies against customer use cases.
• Demonstrate technical feasibility and solution value.
• Document PoC findings and translate successful PoCs into production solution architectures.

Collaboration & Leadership

• Coordinate with Sales, Delivery, Engineering, Product/OEM teams and SMEs.
• Provide technical leadership during strategic opportunities.
• Review architectures and proposals developed by other team members.
• Mentor junior presales consultants and solution architects.
• Maintain reusable solution assets, reference architectures, estimation models and proposal templates.
• Conduct internal technical reviews before customer submission.

Required Experience

• 10+ years of overall experience in Data Management, Data Engineering, Analytics, AI/ML or related technology areas.
• Strong experience in Presales, Solution Architecture or Technical Consulting.
• Proven experience handling enterprise RFP/RFI responses.
• Strong understanding of modern enterprise data architectures.
• Experience designing both on-premises and cloud-based solutions.
• Experience with Data Lake, Data Warehouse and Lakehouse architectures.
• Strong understanding of ETL/ELT, CDC, APIs and streaming integration.
• Understanding of Data Governance, Data Quality, Metadata, Lineage and MDM.
• Exposure to AI/ML, Generative AI and modern LLM-based solution architectures.
• Experience developing technical proposals, architecture diagrams, project estimates and resource plans.
• Experience interacting directly with enterprise customers and senior stakeholders.

Preferred Skills

• Enterprise architecture and solution-design methodologies.
• Cloud architecture experience across Azure, AWS and/or GCP.
• Microsoft Fabric / Databricks / Snowflake / Cloudera exposure.
• Informatica and/or Qlik Talend ecosystem experience.
• Kafka, Spark, Airflow and modern data engineering frameworks.
• Data Governance and MDM platforms.
• GenAI, RAG, LLM, Vector DB and Agentic AI concepts.
• DevOps/DevSecOps and CI/CD for data platforms.
• Kubernetes/OpenShift/container-based platforms.
• Security and HA/DR architecture.

Key Competencies

The successful candidate should demonstrate:

• Solution thinking: Ability to convert ambiguous business requirements into practical technical solutions.
• Architecture capability: Ability to design complete end-to-end architectures rather than individual technology components.
• Presales mindset: Ability to balance technical excellence, customer requirements, delivery feasibility and commercial viability.
• Communication: Ability to explain complex architecture to both technical and executive stakeholders.
• Estimation: Ability to develop realistic implementation plans, resource estimates and sizing assumptions.
• Technology breadth: Strong understanding across data, analytics, cloud and AI technologies.
• Leadership: Ability to coordinate multiple SMEs and technical teams during complex pursuits.
• Proposal ownership: Ability to independently drive the technical portion of strategic bids from requirement analysis through final submission and technical defence.

Typical Deliverables

• RFP/RFI technical responses
• Technical proposals
• Solution architecture documents
• Architecture diagrams
• Technology-stack recommendations
• Compliance matrices
• Clarification questionnaires
• Scope and assumption documents
• Infrastructure sizing and BoQs
• Effort estimates
• Resource loading plans
• Project implementation plans
• PoC plans and success criteria
• Technical presentations and customer demonstrations
• Technical defence presentations

Good to have skills

• Ability to solve complex data problems

Understanding of change data capture and data refresh strategies and processes

Qualifications and Education Requirements

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science or a related discipline.
• Relevant certifications in Cloud, Data Management, Enterprise Architecture, Analytics or AI/ML would be an advantage.