Sr. Principal PreSales Lead – Data Management, Analytics & AI/ML

Edgematics; United States; Remote; USD 180,000 - 280,000; Full time

Job summary

Edgematics is seeking a Senior Principal PreSales Lead for the North American market. You will own the technical strategy, architecture, and executive advisory across major pursuits, coordinating offshore and onshore teams to deliver high-quality RFP defenses and PoCs.

The ideal candidate has 15+ years in data architecture, presales, and strategic consulting, with deep cloud platform experience (AWS/Azure/GCP) and a track record of engaging C-suite stakeholders.

Qualifications

• 15+ years in Enterprise Data Architecture, High-Value PreSales, and Strategic Technical Consulting.
• Experience managing large commercial enterprise pursuits and technical close cycles in North America.
• Deep expertise designing cloud-native data platforms across AWS, Azure, GCP.
• Proven ability to lead global pursuit groups across time zones.

Responsibilities

• Lead technical discovery and presales lifecycle for strategic North American enterprise accounts.
• Deconstruct ambiguous business challenges into modern data architecture roadmaps.
• Deliver architecture walkthroughs, executive pitches and demonstrations to C-level stakeholders.
• Partner with Account Executives to qualify pursuits, map accounts, and mitigate risks.
• Architect scalable multi-cloud data platforms with data governance and security.

Skills

Data Architecture

PreSales

Technical Consulting

Executive Stakeholder Engagement

Education

Bachelor’s or Master’s degree in Computer Science / Information Systems / Engineering

Tools

Databricks

Snowflake

Microsoft Fabric

Cloudera

IBM Cloud Pak for Data

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

The Sr. Principal PreSales Lead is a high-visibility, elite technical sales advisory role tailored for the North American enterprise market. Serving as the primary strategic architect and technical partner to the sales organization, this individual will own the technical strategy, architectural solutioning, and executive-level advisory across major pursuit lifecycles. This role requires an expert blending of technical depth across modern data infrastructures with business acumen to command the trust of Fortune 500 C-suite executives (CIOs, CDOs, CTOs) and drive massive digital transformations.The ideal candidate brings over 15 years of proven excellence across complex presales ecosystems, modern data architecture, and technical consulting. They are highly adept at operating within a sophisticated, multi-time zone global delivery framework, seamlessly orchestrating offshore engineering pods, onshore domain consultants, and strategic OEM alliances to deliver flawless RFP defenses, technical proof-of-concepts, and highly precise, commercially viable effort estimations.

Key Responsibilities :

1. Technical PreSales & Enterprise Customer Engagement

• Lead the complete technical discovery and presales lifecycle for strategic, high-value enterprise accounts across North America.
• Deconstruct highly ambiguous business challenges into rigorous, modern data architecture roadmaps and comprehensive solution capabilities.
• Deliver commanding architecture walkthroughs, executive pitches, and high-impact technical solution demonstrations to C-level stakeholders.
• Partner with Account Executives to proactively qualify pursuits, map accounts, identify technology dependencies, and mitigate architectural evaluation risks.

1. End-to-End Solution Architecture & Ecosystem Design

• Architect highly scalable, multi-cloud modern data platforms incorporating Data Lakes, Data Mesh architectures, Lakehouses (Snowflake, Databricks), and real-time streaming topologies.
• Incorporate enterprise-grade data management structures, including automated Data Quality/Observability pipelines, Master Data Management (MDM), strict Metadata Management, and Data Catalogs.
• Ensure all architectural blueprints conform to rigorous North American enterprise standards: advanced network security (DMZs, Firewalls, VPNs), strict IAM/RBAC models, and regulatory frameworks (CCPA, HIPAA, SOX, GDPR).
• Formulate definitive business continuity paradigms covering High Availability (HA) and Disaster Recovery (DR) models matching stringent RPO/RTO parameters.

1. Enterprise AI/ML, Generative AI & Agentic Architectures

• Drive presales solutioning for advanced analytics and cutting-edge cognitive computing architectures.
• Design production-ready Generative AI topologies featuring advanced Retrieval-Augmented Generation (RAG), vector storage optimization, and secure API gateways.
• Formulate enterprise-wide Agentic AI pipelines, mapping orchestrations between large language models (LLMs), business lines, and transactional databases.
• Embed robust AI safety mechanisms including regulatory alignment, guardrail enforcement, continuous model observability, and human-in-the-loop validation.

1. Bid Management, RFP Defense & Deliverables

• Own and drive the technical execution of large-scale, multi-million-dollar RFPs, RFIs, and complex Statements of Work (SOW).
• Draft clear compliance matrices, explicit assumptions, technical scoping definitions, and exhaustive risk mitigation sheets.
• Lead technical defense sessions to successfully counter competitive alternatives and validate the superiority of proposed designs.

1. Estimation, Commercial Alignment & Sizing

• Orchestrate cross-functional Global Delivery Units (GDUs), aligning onshore pursuit teams with offshore engineering centers of excellence to assemble PoCs.
• Oversee the strategic scoping and technical validation of high-impact Proof of Concepts (PoCs) to prove business value.
• Mentor senior pre-sales engineers and solution architects; build a shared, highly reusable repository of reference architectures, templates, and baseline estimates.

Required Experience & Technical Skills

• 15+ years of accelerating professional experience across Enterprise Data Architecture, High-Value PreSales, and Strategic Technical Consulting.
• Demonstrated success managing large commercial enterprise pursuits and technical close cycles within the North American market.
• Deep expertise designing large-scale cloud-native data platforms across major hyper-scalers (AWS, Azure, GCP).
• Advanced knowledge of modern data platforms: Databricks, Snowflake, Microsoft Fabric, Cloudera, or IBM Cloud Pak for Data.
• Hands-on knowledge or strong conceptual depth across enterprise integration ecosystems: Streaming (Kafka, Spark), Orchestration (Airflow), and ETL/CDC frameworks (Informatica, Talend, Qlik).
• Solid architectural proficiency spanning Data Governance ecosystems, MDM frameworks, and modern AI/ML lifecycle paradigms (MLOps, LLMOps).
• Proven ability to direct complex global pursuit groups, balancing multi-shore resources across diverse timezones seamlessly.

Preferred Qualifications & Certifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, Engineering, or a highly related technical field.
• Enterprise Architecture Framework credentials (e.g., TOGAF, Zachman).
• Professional-level Cloud Solutions Architect credentials (AWS Certified Solutions Architect Professional, Azure Solutions Architect Expert, GCP Professional Cloud Architect).
• Advanced Data Platform certifications (Databricks Certified Solutions Architect, Snowflake Certified Core/Advanced).

Key Competencies

• Strategic Solution Synthesis: Fluidly translating highly ambiguous business pain points into crisp, executable enterprise tech blueprints.
• Commercial PreSales Acumen: Expertly balancing uncompromising architectural integrity with delivery realities and commercial viability.
• Executive Articulation: Exceptional communication power capable of distilling complex data meshes into strategic value streams for Fortune 500 boards.
• Global Orchestration Matrix: Proven capacity to direct diverse technical subject‑matter experts across varied geographies under compressed bidding windows.

Required Experience

• 15+ years of overall experience in Data Management, Data Engineering, Analytics, AI/ML or related technology areas.
• Strong experience in Presales, Solution Architecture & 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, Query Engines, Storage technologies, Table Formats, 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/Cloud Pack for Data.
• Informatica, Data Stage, Qlik Talend & CDC 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.

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

• Python Programming
• Hand on Kubernetes deployment

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.