Delivery Manager, Data, US
Techtorch
| Company | Techtorch |
| Category | Data & Analytics |
| Location | United States |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 18 Feb 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
Delivery Manager, Data, US
TechTorch • United States (Remote)
COMPANY OVERVIEW
TechTorch is a leader in delivering innovative Enterprise Technology solutions, leveraging AI-powered accelerators to drive measurable business success for Private Equity-backed companies. Our experts specialize in Commercial Excellence (Lead-to-Cash, Quote-to-Cash), Data & Business Intelligence, and AI-enabled transformations. We disrupt the system integration space by embedding high-caliber delivery teams inside PE portfolio companies to drive EBITDA improvement and sustainable revenue growth.
POSITION OVERVIEW
The Delivery Manager (Data Practice) is a senior client-facing leader who owns end-to-end project delivery for TechTorch's data, business intelligence, and AI engagements. You are the connective tissue between C-suite client stakeholders and multi-disciplinary delivery teams — setting the vision, managing complexity, and driving outcomes on high-stakes data transformation projects for PE-backed enterprises.
This role requires a practitioner who has led data-intensive projects in a consulting or professional services environment and can operate with dual fluency: deep enough on the technical side to challenge data architects and engineers, and credible enough on the business side to shape strategy with executive stakeholders. You bring a structured consulting mindset to messy, ambiguous client environments — and you know how to get things done.
We are targeting professionals with 5–7 years of experience from top consulting firms (Accenture, Deloitte, McKinsey, BCG, Bain, or comparable) who are ready to move from advising to owning delivery in a fast-moving, PE-focused environment.
KEY RESPONSIBILITIES
Data Project Leadership & Delivery
- Own end-to-end delivery of data, BI, and AI projects — from discovery through go-live — for PE-backed enterprise clients.
- Manage multi-geography and multi-level data complexity, including consolidating data across business units, enterprise systems, and reporting hierarchies.
- Lead specialized data delivery workstreams (business intelligence, data warehouse builds, KPI frameworks, AI application readiness) with a focus on measurable business outcomes.
- Oversee the quality and completeness of data deliverables, applying knowledge of conceptual and physical data models, aggregation logic, and hierarchy structures.
Client Engagement & C-Level Communication
- Serve as primary day-to-day client relationship owner for data engagements, building trust with functional leaders and C-suite sponsors.
- Co-create solutions and implementation roadmaps with C-level executives, translating data capabilities into business value narratives.
- Communicate project status, design decisions, risks, and escalations on a weekly basis to executive stakeholders and board members.
- Conduct workshops to align clients on data strategy priorities, KPI definitions, and reporting governance.
Team & Cross-Functional Management
- Lead and coordinate multidisciplinary delivery teams including data engineers, architects, BAs, and client-side resources across time zones.
- Bring in specialized data experts (e.g., data architects, BI developers) at the right stages of pre-sales and delivery, ensuring the right expertise is deployed at the right time.
- Mentor and develop Business Analysts on data projects, building capability across the team.
- Collaborate with TechTorch Managing Directors and Client Account Leads to ensure delivery excellence and identify expansion opportunities.
Technical Oversight & Solutioning
- Assess data source quality, model architecture, and BI layer design — and make informed decisions about trade-offs, escalations, and technical dependencies.
- Review and challenge data models, KPI logic, and visualization frameworks to ensure they serve business objectives and are built to scale.
- Evaluate build-vs-configure decisions and partner with solution