---
title: 'Data Product Manager at AHEAD'
canonical: 'https://feeny.ai/job/data-product-manager-ahead-united-states-7pnbetayn71h'
type: 'job'
last_seen: '2026-11-06'
---

# Data Product Manager at AHEAD

- **Company:** AHEAD
- **Location:** United States
- **Compensation:** $150k–$175k
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-08-04
- **Last confirmed live:** 2026-11-06
- **Apply:** https://jobs.lever.co/thinkahead/9945b21f-fdf8-4458-b097-c60fc0e3b237

## Job description

The Data Product Manager will help AHEAD turn its data into trusted, discoverable and reusable products that solve business problems. Reporting to the Director, Data Platform, this role works with Data Platform engineering, Analytics and domain teams to set priorities, define requirements and help consumers use data effectively. This is a hands-on individual-contributor role. You will work directly with consumers, examine existing data assets, define useful products, maintain product documentation and catalog content, and help teams deliver and improve those products throughout their lifecycle. Governance is an essential part of the role: making sure consumers understand what a product means, whether they can trust it, and how to access and use it appropriately. Your governance responsibilities cover data products delivered or published through the Data Platform, within existing enterprise policies. You will apply agreed policies through practical product standards and discovery workflows, partnering with engineering, Security and domain owners on supporting controls.

Duties and Responsibilities

Product discovery, strategy and prioritization

- Work with business stakeholders, analysts, application teams and other data consumers to understand their decisions, workflows and unmet needs; distinguish a reusable data product opportunity from a one-off reporting or integration request.

- Define product problems, target consumers, expected value and success measures, evaluating existing assets for reuse before proposing new development.

- Own the data product roadmap and product priorities within the strategy and capacity agreed with the Director, Data Platform; balance business value, urgency, risk, dependencies and ongoing support costs.

- Own product goals, priorities and requirements; partner with the Product Owner, who manages day-to-day backlog coordination, intake and delivery dependencies, using one shared backlog.

Product delivery and lifecycle

- Translate consumer needs into engineering-ready requirements and acceptance criteria covering business definitions, data scope and granularity, freshness, quality, access and supported consumption methods.

- Partner with Data Platform engineers, Analytics and source-system teams to scope practical releases, resolve dependencies, validate outputs with consumers and communicate delivery trade-offs.

- Manage the product lifecycle from discovery through launch, adoption, improvement and retirement, including change communication and the impact of schema or definition changes on consumers.

- Partner with Analytics and domain owners to identify authoritative business definitions and align reusable datasets and semantic models, preserving useful existing capabilities and resolving inconsistencies where they matter.

Governance and product trust

- Define and apply lightweight product publication and readiness standards, including accountable owners, business definitions, classification, source and lineage information, quality and freshness expectations, access instructions and lifecycle status.

- Establish named business/domain owners who remain accountable for data meaning, quality expectations and appropriate-use or access decisions within policy. Coordinate stewardship and document those decisions.

- Define governance and access requirements with Security, IAM and engineering, including approval paths, sensitive-data protections and traceability; validate that delivered products meet the agreed requirements.

- Prioritize quality and governance improvements based on consumer impact and risk. Engineers implement the supporting checks, monitoring, lineage capture and technical controls.

Discovery, self-service and adoption

- Maintain a useful inventory of data products and directly create or configure catalog entries, glossary terms, product documentation and onboarding workflows using available tools.

- Own the consumer experience requirements for finding, understanding and requesting access to trusted data, including business-friendly discovery for users who do not work directly in Snowflake.

- Evaluate existing catalog and metadata capabilities, identify practical gaps and prioritize incremental improvements before proposing new tools or custom development.

- Support launch communications and consumer onboarding; use feedback and practical indicators of usage, quality and access friction to guide improvements.

Education and Experience

-

- Bachelor's degree or equivalent practical experience.

- Five or more years of relevant experience across data product management, analytics, data platforms, analytics engineering, data governance or related disciplines, with experience shaping priorities, requirements or cross-functional delivery; a formal product management title is not required.

- Practical experience helping deliver and improve data products or platform capabilities in response to consumer needs.

- Strong skills in consumer discovery, problem definition, prioritization, requirements, acceptance criteria and stakeholder alignment.

- Technical fluency in cloud data platforms, pipelines, data modeling, semantic layers and consumption patterns, with working SQL skills sufficient to investigate data and validate product behavior.

- Practical experience applying ownership, metadata, lineage, quality, classification and access requirements to data products, and maintaining product documentation, catalog content or discovery workflows.

- Ability to translate between business and technical audiences, negotiate competing priorities and influence teams without direct authority.

- Ability to make progress independently in a small, resource-constrained team, using lightweight processes and balancing new capabilities with operational commitments.

## Preferred qualifications

- Experience with Snowflake, dbt and Power BI, or comparable cloud data and analytics platforms.

- Hands-on experience configuring or onboarding assets into a data catalog, business glossary or metadata management tool; no specific vendor is required.

- Experience improving governed self-service access in partnership with Security and IAM teams.

- Experience supporting shared business definitions and reusable semantic models across teams or domains.

- Familiarity with data products consumed through APIs or AI tools, including their access, quality and traceability considerations.

What success looks like

- Reusable data products are delivered, adopted and demonstrate measurable business value, such as time saved, reduced manual work or improved reporting accuracy.

- The team has a prioritized, achievable product roadmap tied to clear consumer problems and business outcomes.

- Consumers can find important products, understand their meaning and limitations, and identify how to obtain appropriate access.

- Published products have clear ownership and proportionate quality, metadata and access expectations.

- Analytics, engineering and business owners use an agreed approach to shared definitions and product changes.

- Consumer feedback and practical usage, quality and access indicators inform product improvements.

## About AHEAD

## Company Overview
- **One-liner**: AHEAD is an engineering-led digital platform company that accelerates enterprise strategy into execution across AI, cloud, data, security, and infrastructure.
- **Entity Type**: Private (Bootstrapped/PE-backed; no public funding rounds disclosed)
- **Headquarters**: New York, New York, USA
- **Founded**: 2007
- **Founders**: Dan Adamany (CEO)

## Core Business
- **Primary industry/industries**: IT Services & Consulting, Digital Transformation, Managed Services
- **Target customers**: Fortune 1000 enterprises, large-scale organizations with complex, multi-domain IT estates (B2B, Enterprise)
- **Mission or purpose statement**: To accelerate strategy into execution, engineering integrated solutions across infrastructure, applications, data, and security — building what others only blueprint.

## Products & Services
- **AI Transformation**: A unified AI fabric to accelerate AI from idea to business value, including AI-enabled infrastructure and data readiness. *(Service)*
- **AI Enabled Infrastructure**: Scalable, resilient architectures supporting high-performance workloads from core to edge. *(Service)*
- **Data Platform Modernization**: Governed data platforms that turn raw data into trustworthy insight and AI readiness. *(Service)*
- **Secure and Resilient Architectures**: Platforms designed to reduce risk, limit impact, and recover quickly. *(Service)*
- **Platform and Workload Modernization**: Modernizing platforms and optimizing workloads across cloud, data center, and edge. *(Service)*
- **Operational Excellence**: Frictionless operations, predictable performance, and optimized spend. *(Service)*
- **Managed Services**: Ongoing management of critical systems over their entire lifecycle. *(Service)*
- **Proprietary IP (Foundry™, Hatch™)**: Accelerators, financial models, scorecards, integration-ready code, and policy-as-code. *(Software/Tooling)*
- **400+ APIs & Custom Offerings**: Frameworks that integrate multiple platforms for automation, data sandboxes, and ML/AI exploration. *(Platform)*

## Market Standing
- **Valuation/Market Cap**: Not publicly available (Private company)
- **Key Metric**: **Gross Revenue** of **$3.7 billion** (as of 2024, following the acquisition of CDI); **2,500+ employees** across 40 locations globally.
- **Notable Investors/Partners**: Partners with **200+ technology providers** (e.g., major cloud, data center, security, and automation vendors). The company is backed by private equity (likely a growth/PE structure, though specific investors are not named in the provided materials).
- **Growth Signals**: Scaled from a Midwest focus to national and international coverage through **12 acquisitions since 2019**; expanded service portfolio into data, app dev, custom manufacturing, and global logistics via M&A; recent acquisition of CDI (New York-based) added significant scale.

## Competitive Advantages
- **Orchestration Expertise**: Ability to stitch together complex, multi-vendor systems into cohesive, scalable architectures — a differentiator in an increasingly fragmented IT landscape.
- **Full-Stack Engineering**: Deep expertise across AI, cloud, data, security, infrastructure, and operations, applied in an integrated fashion.
- **Unified Delivery Model**: One team, one roadmap, one owner held accountable for driving outcomes, from strategy through implementation and ongoing operations.
- **Consultative Approach**: Engages early to architect transformation roadmaps, not just as a reseller of hardware/software.
- **Proprietary IP (Foundry™, Hatch™)**: Unique accelerators and code libraries that de-risk and speed up client digital initiatives.

## Strategic Focus
- **Current priorities**: Accelerating enterprise AI adoption; expanding managed services; deepening capabilities in data, security, and cloud; continuing M&A strategy to add geographic coverage and new service lines.
- **Direction for growth**: Becoming the go-to strategic partner for Fortune 1000 leaders navigating the complexity of modern IT, with a focus on accountability from design to operations.

## Why Work Here
- **Culture highlights**: Engineering-led organization with a strong emphasis on technical depth, ownership, and accountability. Described as a "game-changer in tech" that values innovation and execution.
- **Remote/hybrid/office policy**: Likely hybrid/office-based given the nature of client-facing consulting and infrastructure work; 40 global locations suggest flexibility in location.
- **Notable perks or engineering culture**: Opportunity to work with cutting-edge technologies across AI, cloud, security, and data at massive scale; exposure to Fortune 1000 clients and complex transformations; strong focus on IP development and engineering excellence; clear growth trajectory through acquisitions and expansion.

## Sources
1. [AHEAD Official Website](https://www.ahead.com/)
2. [AHEAD Story Page](https://www.ahead.com/story/)
3. [AHEAD Leadership Page](https://www.ahead.com/leadership/)
4. [AHEAD Careers Page](https://jobs.lever.co/thinkahead)

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