Job Description – Delivery Manager (External Data & Integration)

Job Title 0 Delivery Manager – External Data Integration & Vendor Strategy

Location - Toronto, ON (Hybrid)

Role Summary
We are seeking a Delivery Manager – Extkernal Data Integration to lead the end-to-end lifecycle of sourcing, acquiring, integrating, and operationalizing external data within our Enterprise AI Data Platform (Microsoft Fabric & Azure AI Foundry).
This role will focus on enabling high-impact business use cases by integrating external datasets (e.g., market data, macroeconomic indicators, demographic insights, rental intelligence) from providers such as CBRE, JLL, CoStar, and similar vendors into a centralized Fabric Data Hub, and ensuring these datasets are transformed into analytics- and AI-ready products.

The ideal candidate will operate at the intersection of business, data, vendors, and engineering, driving both vendor engagement and technical delivery governance to ensure external data is consistently ingested, standardized, and made consumable across enterprise use cases.

Key Responsibilities
1. External Data Strategy & Requirements
• Partner with business stakeholders (Asset Management, Investments, Research, etc.) to:
o Identify external data needs aligned to business use cases
o Assess current sourcing methods and gaps in data availability
• Define data acquisition strategy for each use case (buy vs. build vs. partner)
• Establish a prioritized roadmap of external data integrations across projects

2. Vendor Evaluation & Procurement Enablement
• Lead evaluation of external data vendors (e.g., CBRE, JLL, CoStar, economic data providers)
• Compare vendor datasets across:
o Coverage, granularity, frequency, quality, and licensing constraints
• Partner with:
o Procurement teams (vendor onboarding and pricing)
o Legal teams (data licensing agreements, usage rights)
o Vendor governance teams (risk, compliance, security)
• Support contract structuring to ensure:
o Scalability of usage across enterprise
o Alignment with AI and analytics consumption needs

3. Data Integration & Standardization Strategy
• Define the end-to-end data ingestion strategy into Microsoft Fabric:
o API ingestion, data feeds, file-based ingestion, connector-based approaches
• Establish patterns for integrating multi-vendor datasets with overlapping domains
• Define standardization and harmonization rules across:
o Data structures
o Metrics definitions
o Time series alignment
o Geographic hierarchies
• Ensure alignment with Medallion Architecture:
o Bronze: Raw ingestion from vendors
o Silver: Cleansed, standardized datasets
o Gold: Business-ready, domain-specific models
(Aligned to your Fabric integration approach and Lakehouse design patterns found in internal architecture
docs) [Integratio...Dashboard | Word]

4. Delivery Management & Execution
• Act as the Delivery Lead for external data integration initiatives:
o Define project scope, milestones, and deliverables
o Track execution across multiple parallel vendor integrations
• Coordinate across:
o Data Engineering teams (pipeline development)
o Data Architects (modeling and standards)
o AI/Analytics teams (downstream consumption)

• Ensure delivery of:
o Reliable pipelines
o High-quality datasets
o Clear documentation and lineage
5. Architecture Definition & Documentation
• Define and document:
o Data ingestion architecture
o Transformation and standardization layers
o Cross-domain data models

• Translate business needs into technical architecture for Data Engineers to implement
• Ensure solutions are:
o Scalable
o Reusable across projects
o Aligned with enterprise standards (Fabric + AI Foundry)

6. Data Governance, Quality & Compliance
• Ensure all external data integrations comply with:
o Data privacy regulations
o Licensing agreements
o Internal governance standards
• Define data quality expectations and validation rules
• Establish monitoring and reporting for:
o Data freshness
o Data completeness
o Vendor reliability

7. Cross-Functional Stakeholder Engagement
• Act as the primary interface between:
o Business stakeholders
o Vendors
o Engineering teams
o Legal / procurement functions
• Communicate architecture decisions and trade-offs clearly to both technical and non-technical audiences
• Operate effectively within a federated delivery model, enabling multiple teams to leverage shared datasets

Required Qualifications
Experience
• 8+ years of experience in:
o Data delivery / program management / integration roles
o OR consulting roles focused on data platforms / analytics
• Proven experience working with:
o External data providers and vendor ecosystems
o Data procurement and contract coordination
• Experience delivering projects involving:
o Data integration or data platform implementations

Technical Knowledge
• Strong understanding of:
o Data ingestion patterns (APIs, batch, streaming, connectors)
o Data transformation frameworks (ETL / ELT)
o Medallion architecture or similar layered models
• Experience working with:
o Microsoft Fabric, Azure Data platforms, or similar ecosystems
• Ability to translate business data requirements into technical solutions

Business & Vendor Skills
• Experience evaluating and comparing third-party datasets
• Strong understanding of:
o Data licensing models
o Vendor negotiations (in partnership with procurement/legal)
• Ability to balance business value vs. cost for external data investments

Project & Delivery Skills
• Strong delivery management and execution discipline
• Ability to manage multiple parallel initiatives (iterative vendor onboarding model)
• Experience working in cross-functional, matrixed environments

Nice-to-Have
• Experience in:
o Real estate, investment, or financial data domains
o Macro-economic or demographic datasets
• Exposure to:
o AI/ML-driven analytics use cases
o Data products or data-as-a-service models
• Familiarity with:
o Semantic models, AI data agents, or analytics consumption layers