About Woodland Mills

Woodland Mills is a global manufacturer of innovative forestry equipment, committed to making high-quality solutions accessible to property owners everywhere. We combine engineering expertise with a customer-focused approach, delivering dependable products, and dedicated support. Our team values authenticity, resourcefulness, and continuous improvement, striving to create a straightforward and rewarding experience for every customer.

Role Mandate

Build and govern a trusted enterprise data foundation that turns operational data from ERP, CRM, ecommerce, service, logistics and other systems into secure, reusable data products.

Position overview The Data Analytics Architect designs, develops and supports the organization's modern analytics platform. The role establishes reliable data flows from operational systems into Microsoft Fabric, organizes data through governed lakehouse and warehouse patterns, and delivers trusted semantic models and Power BI reporting experiences. Working across business and technical teams, the Architect translates reporting and analytical needs into scalable data products while improving data quality, lineage, security, performance and adoption.

This role suits a practical builder who can move between architecture, engineering, analysis and stakeholder conversations.

Key responsibilities

1. Data architecture and platform design

· Design and maintain a practical enterprise data architecture using Microsoft Fabric, aligned to business priorities, source-system realities and security requirements. · Define clear separation between raw, validated and curated data, using lakehouse and warehouse patterns appropriate to the structure, scale and consumption needs of each domain.

· Develop reusable data-domain models for areas such as customers, products, sales, inventory, purchasing, service, finance, logistics and digital engagement.

· Establish conventions for workspaces, naming, environments, storage, refresh, orchestration, ownership and lifecycle management.

1. Data integration and engineering

· Build and support ingestion and transformation pipelines from Dynamics 365 Business Central, Dynamics 365 Customer Engagement, Dataverse, ecommerce, Google Analytics, SharePoint, files, APIs and other operational sources. · Create reliable transformation logic for cleansing, standardization, deduplication, conformance, historization and business-rule application.

· Implement incremental processing, scheduling, dependency handling, logging, alerting and recovery patterns that improve reliability and supportability.

· Partner with application owners to resolve source-data issues while preserving traceability between source records and analytical outputs.

1.



Data warehousing and modelling

· Design dimensional and analytical models that provide consistent facts, dimensions, keys, hierarchies and business definitions. · Create curated warehouse and lakehouse structures optimized for Power BI, ad hoc analysis and downstream data products.

· Maintain shared business calculations and measures so that key metrics are defined once and reused consistently.

· Balance usability, performance, maintainability and cost when selecting storage, transformation and serving patterns.

1. Power BI and semantic modelling

· Develop governed Power BI semantic models, reports and dashboards that answer operational and strategic questions. · Use effective model relationships, DAX, calculation logic, row-level security and refresh design to deliver trusted analytics.

· Promote a thin-report and reusable-model approach where practical, reducing duplicated logic and inconsistent metrics.

· Coach business users on interpreting metrics, navigating reports and using certified or endorsed datasets for self-service analysis.

1. Data governance, quality and security

· Define and monitor data-quality controls, including completeness, validity, uniqueness, timeliness and reconciliation checks. · Document lineage, transformations, business definitions, ownership, access rules and known limitations for key data products.

· Apply least-privilege access, appropriate workspace and item permissions, and secure handling of confidential or regulated data.

· Support retention, audit, privacy and compliance needs in collaboration with business, IT and leadership stakeholders.

1. Delivery, support and continuous improvement

· Gather and prioritize analytical requirements, convert them into deliverable data products, and communicate trade-offs clearly to technical and non-technical audiences. · Use source control, peer review, testing and structured deployment practices to improve quality and reduce change risk.

· Monitor platform health, pipeline execution, refresh performance, capacity use and report adoption, then recommend targeted improvements.

· Create architecture diagrams, runbooks, data dictionaries, support documentation and user guidance that make the platform sustainable.

Qualifications

· Bachelor's degree or diploma in Information Technology, Data Science, Computer Science, Business Analytics or a related field,



or equivalent practical experience.

· Demonstrated experience in data engineering, data warehousing, business intelligence, analytics engineering or a comparable role.

· Hands-on experience with Microsoft Fabric and Power BI, including data ingestion, transformation, modelling, semantic models and report development.

· Robust understanding of dimensional modelling, star schemas, data quality, master and reference data, metadata, lineage and analytical governance.

· Working knowledge of SQL and DAX. Experience with Power Query M, Python, notebooks, Spark or KQL is an asset.

· Experience integrating ERP, CRM and SaaS data. Familiarity with Dynamics 365 Business Central, Dynamics 365 CE, Dataverse, SharePoint and Power Platform is an asset.

· Ability to diagnose data discrepancies and performance issues across source, transformation, model and reporting layers.

· Strong communication and facilitation skills, with the ability to turn ambiguous business questions into clear data requirements and explain technical concepts to non-technical audiences.

· Detail-oriented and organized, with the ability to manage multiple priorities while maintaining documentation and delivery discipline.

Preferred capabilities

Technical:

- Fabric Lakehouse and Warehouse
- Data Factory piplines and Dataflows Gen2
- Power BI semantic modelling and DAX
- SQL, Power Query and data transformation
- GIT-based source control and deployment practices
- Montioring, performance tuning and capacity awareness

Delivery and Business:

- Requirements discovery and metric definition
- Data-product ownership and lifecycle thinking
- Data-quality investigation and reconcilliation
- Cross-functional stakeholder facilitation
- Documentation, training and adoption
- Prioritization based on business value and risk

Work Location: This is a hybrid position, with work performed partly in the office and partly from home. During the first few months, the successful candidate will be expected to work in the office more frequently to support onboarding, training, and integration with the team.

Additional Information:

A criminal record check will be required for the successful candidate as part of the hiring process.

We thank all applicants for their interest; however, only those selected for an interview will be contacted. If you require accommodation during any stage of the recruitment process, please inform us.

Pay: $70,000.00-$90,000.00 per year

Experience

- Data engineering, warehousing, BI, or analytics engineering: 3 years (preferred)
- Microsoft Fabric & Power BI: data pipelines, models, reports: 3 years (preferred)

Work Location: Hybrid remote in Port Perry, ON

📌 Data Analytics Architect (Port Perry)
🏢 Woodland Mills
📍 Port Perry