Senior Director (Hartford)

Role: Senior Director
Location: Hartford, Connecticut, USA
Reporting to: AVP level.

Job description:
Tango Leader – PreSales Lead, Data & Analytics

Role Overview
The PreSales Lead – Data & Analytics is a senior, client-facing leadership role.
Responsible for driving revenue growth through strategic account mining and solution-led presales.
Leads end-to-end presales pursuits for Data & Analytics opportunities.
Acts as a bridge between business, technology, sales, and delivery teams.
Converts qualified opportunities into scalable, profitable, and governable engagements.
Plays a key role in mentoring presales teams and ensuring smooth transition from deal shaping to delivery.
Key Objectives
Drive revenue growth within strategic and key enterprise accounts.
Establish the organization as a trusted Data & Analytics transformation partner.
Ensure strong deal governance and architectural alignment from presales to delivery.
Support talent identification and onboarding aligned with account and solution needs.
Detailed Roles & Responsibilities
1. Account Mining & Revenue Growth
Collaborate closely with Account Managers, Client Partners, and Sales Leadership.
Proactively mine existing client accounts to identify:
Whitespace opportunities
Expansion, cross-sell, and up-sell opportunities
Develop deep understanding of:
Client business models and industry context
Client’s data landscape, maturity, and challenges
Identify and shape value-led Data & Analytics use cases such as:
BI and reporting modernization
Advanced analytics and predictive insights
AI/ML and data science solutions
Cloud data platform modernization
Build and maintain a strong pipeline with predictable revenue outcomes.
Support revenue growth across analytics, cloud, and data engineering service lines.
2. Solution Definition & Deal Shaping
Own solution architecture and deal definition for complex Data & Analytics opportunities.
Design end-to-end solutions across:
Data platforms, lakes, and warehouses
BI, dashboards, and reporting layers
Advanced analytics, AI/ML, and data science use cases
Cloud ecosystems (AWS preferred)
Generative AI–based solutions
Define:
Technical architecture
Operating model and delivery approach
Phasing and roadmap
Lead effort estimation, pricing, commercials, and staffing models.
Ensure solutions are:
Client-value driven
Technically feasible and scalable
Commercially viable and profitable
Clearly articulate solution value propositions to:
Senior business stakeholders
Technology and architecture leaders
3. Proposal Leadership & Sales Support
Lead and own end-to-end proposal creation for:
RFPs, RFIs, and RFQs
Client presentations and solution decks
Develop compelling:
Storyboards
Solution narratives
Differentiation messaging
Lead:
Solution walkthroughs
Technical discussions
Executive and CXO-level presentations
Work closely with Sales, Marketing, and Delivery teams to improve:
Proposal quality
Win ratios
Time-to-response
Ensure proposals comply with:
Organizational standards
Risk and compliance guidelines
Delivery capabilities and constraints
4. Team Mentoring & Capability Building
Mentor and coach:
Solution Architects
Presales Consultants
Analysts and junior team members
Build strong capabilities in:
Solution design
Estimation and commercials
Client storytelling
Develop reusable:
Solution frameworks
Accelerators
Presales artifacts and templates
Coach teams on:
Client communication and executive presence
Storytelling and value articulation
Foster a culture of:
Continuous learning
Quality improvement
Innovation in solutioning
5. Delivery Governance & Deal-to-Execution Transition
Support seamless transition from presales to delivery teams.
Ensure original solution intent and commercials are preserved.
Participate in:
Architecture reviews
Design validations
Governance forums
Act as an escalation point for:
Solution gaps
Scope clarifications
Architectural or commercial concerns
Ensure early delivery aligns with:
Committed scope
Architecture
Timelines and commercials
Provide advisory support during:
Critical delivery milestones
Steering committee meetings
Audits or risk reviews
Required Skills & Experience
Experience
Overall IT consulting experience.
Data & Analytics presales, solutioning, or consulting roles.
Proven history of:
Account mining
Revenue generation
Deal closures
Experience working with large enterprises and CXO-level stakeholders.
Technical & Domain Expertise
Strong knowledge of Data & Analytics ecosystem, including:
Data warehousing and BI solutions
Cloud data platforms (AWS preferred)
Modern analytics stacks (Snowflake, Databricks, etc.)
Good understanding of:
ETL and data integration concepts
Data governance, quality, and security
Advanced analytics and AI/ML use cases
Property & Casualty (P&C) Insurance domain experience is a strong plus.

PreSales & Consulting Skills
End-to-end solution architecture and estimation.
Proposal and bid management.
Executive-level client communication and storytelling.
Strong commercial awareness and pricing constructs.
Effective stakeholder management across sales, delivery, and clients.
Key Competencies
Strategic and entrepreneurial mindset.
Strong analytical and problem-solving abilities.
Ability to influence without formal authority.
High degree of ownership and accountability.
Comfortable working in fast-paced and ambiguous environments.
Success Measures
Revenue growth and deal conversion ratios.
Quality, scalability, and reusability of proposed solutions.
Client satisfaction and repeat business.
Smooth and effective transition from deal closure to delivery execution.