About Us:
We are a leading ERP software and solutions provider to dealers and rental companies of heavy equipment. We specialize in working with the construction, mining, forestry, material handling, and agriculture industries. We aim to be the ERP thought leader in our space and a trusted IT advisor to all dealers and rental companies. Today, we have over 750 employees, offices on four continents, and customers in over 20 countries. We are privately held, and our headquarters are in beautiful Cary, NC. We are actively seeking talented individuals to join our team and help us aggressively grow our North American footprint for both our on-premises and 100% cloud-based ERP solutions.
Why work for VitalEdge?
We don’t just sell technology, we enable transformation that results in broader societal benefits like building homes and critical infrastructure, growing food and delivering all sorts of products we all rely on for daily life. We exist to ultimately equip the world to keep running. We have more than 60 years of combined experience and two industry-leading software suites and associated apps, with which we will drive the market forward. It’s an exciting time to work for VitalEdge – join us!
Position Overview:
The Data & Analytics Product Manager owns the end‑to‑end data product strategy for a modern heavy‑equipment dealership platform. This role is responsible for transforming raw operational data from core dealer systems into trusted, governed, AI‑compatible data products that power dashboards, analytics, and intelligent agents.
The role sits at the intersection of dealer business operations (Sales, Service, Parts, Rental), Microsoft Fabric‑based data architecture, and Power BI for semantic modeling, ensuring data is not only reported—but actionable, predictive, and consumable by AI.
Responsibilities:
Key Responsibilities
1. Data Product Strategy & Vision
- Define and own the data product roadmap aligned to dealership outcomes such as margin optimization, asset utilization, service productivity, inventory health, fleet optimization
- Establish domain‑based data products (Sales, Service, Parts, Rental, Finance) with clear ownership and success metrics.
- Translate dealer pain points into analytics, KPIs, and AI‑ready data capabilities, not just reports.
2. Microsoft Fabric & Lakehouse Ownership
- Own the Data Lakehouse strategy
- Define standards for:
- Data ingestion from core applications (ERP/DMS, CRM, Rental, Telematics).
- Entity mapping (Customer, Equipment, Work Orders, Parts, Assets).
- Data quality, lineage, and governance.
- Partner with Data Engineering to prioritize pipelines that unlock business value, not just data availability.
3. Semantic Layer & Power BI
- Own the enterprise semantic model used across Power BI, self‑service analytics, and AI agents.
- Ensure:
- Consistent KPI definitions across departments.
- Role‑based metrics for executives, managers, and frontline leaders.
- Reusable, well‑documented datasets that reduce report sprawl.
- Drive adoption of action‑oriented dashboards used in daily operations, not just monthly reviews.
4. AI‑Ready Data & Copilot Enablement
- Design semantic models that are compatible with AI and Copilot experiences, enabling:
- Natural language querying.
- Automated insight generation.
- Anomaly detection and trend identification.
- Partner with AI and product teams to enable data‑driven agents that surface insights instead of static reports.
5. Stakeholder & Cross‑Functional Leadership
- Act as the single point of accountability for analytics outcomes across Product, Engineering, GTM, and Customer Success.
- Work closely with:
- Engineering (data pipelines, Fabric optimization).
- BI Analysts (dashboard design, KPI validation).
- Business leaders (Sales, Service, Parts, Rental) ensure relevance and adoption.
- Balance short‑term reporting needs with long‑term data platform scalability.
Required Skills & Education:
Data & Analytics
- Hands‑on experience with:
- Microsoft Fabric
- Lakehouse architectures
- Power BI semantic models
- Ability to translate operational workflows into data models.
- Strong grasp of:
- Dimensional modeling
- KPI governance
- Data quality and metric consistency
- Experience designing data models for AI and natural language interaction
Product Management
- Proven product management experience owning data platforms or analytics products.
- Ability to define roadmaps, prioritize backlogs, and measure business impact.
- Comfortable operating between technical and business stakeholders.
Deep understanding of heavy equipment dealership operations is a plus.
- Machine sales & rental
- Service operations and technician productivity
- Parts inventory and fill rates
- Asset utilization and lifecycle profitability
…