Category: IT Services
Location: Montreal Quebec Canada
Please note
- It is a 100% Remote position in Canada.
- Candidates Preferred from EST/CST TimeZone.
Job Summary
We are seeking a Consulting Senior Data Architect with deep, production-grade Microsoft Fabric experience to accelerate our active rollout of Fabric for customer-facing and revenue-impacting digital products hosted in Azure. This is a hands‑on role responsible for designing and building Fabric artifacts (pipelines, lakehouses, eventstream/real‑time patterns), defining data architecture standards (conceptual/logical/physical), and implementing governance and security guardrails that scale across multiple product teams.
Key Responsibilities
- Microsoft Fabric Enablement (Hands-onDelivery + Standardization)
- Architect and implement Fabric solutions for data engineering (Spark), Data Factory pipelines , and real-time analytics / Event streams aligned to digital product needs.
- Build and standardize Fabric patterns for ingestion, transformation, and serving across workloads including operational analytics, near-real-time, batch, and data science/ML.
- Create repeatable reference implementations for common digital product scenarios (IoT telemetry, time series, transactional + event fusion, documents, geospatial).
- Unified Data Platform Architecture (TargetState + Roadmap)
- Produce and maintain the target-state architecture for Fabric-based data platform capabilities.
- Define domain-oriented data product patterns including how shared/enterprise datasets are curated and reused.
- Establish architectural boundaries and integration guidance for shared datasets vs. product-owned datasets.
- Data Modeling Standards (Conceptual / Logical/ Physical)
- Define and enforce data modeling standards and templates appropriate to Fabric Lakehouse/Warehouse patterns and product analytics needs.
- Provide modeling guidance for high-variance data types (telemetry, geospatial, documents) and hybrid operational-analytics use cases.
- Define standards for schema evolution, versioning, and contract-first data interfaces (where applicable).
- Governance, Security, and Compliance byDesign
- Design and implement a governance model covering classification, retention, lineage, and auditability.
- Ensure compliance guardrails are built into delivery patterns and operational processes to meet GDPR, ISO 27001, and data residency requirements.
- Define and enforce Fabric access controls using Entra ID, RBAC, and workspace-level controls (including guidance for separation of duties and least privilege).
- CI/CD + Infrastructure as Code (IaC) forFabric
- Define and implement a CI/CD approach for Fabric artifacts as the enterprise source of truth.
- Establish release patterns for Fabric changes (promotion strategy, environment separation, approvals, and quality gates) aligned to platform standards.
- Manage Fabric-related platform configuration using Terraform as the IaC approach (including reusable modules/patterns).
- Create golden path templates and guidance that product teams can adopt with minimal friction.
- Capacity Planning, Cost Model, andChargeback/Show back
- Design Fabric capacity strategy (SKU sizing, workload isolation, scaling model) to support multiple products reliably.
- Define guardrails and operational practices that reduce waste and improve predictability.
- Reliability, Observability, and OperationalReadiness
- Define reliability patterns and operational standards for data pipelines and real-time workloads.
- Integrate logging/monitoring with Log Analytics and security monitoring with Sentinel, including alerting and incident response considerations.
- Define and operationalize data quality SLAs (freshness, completeness, accuracy, timeliness) and embed quality checks into delivery pipelines.
- Consulting Engagement + Governance Forums
- Participate in architectural governance and provide architecture review/sign-off, with authority to mandate standards when necessary to protect platform integrity
- Partner closely with platform engineering to align patterns across identity, network, DevOps, and security.
- Working Style & Mindset
- Hands‑on architect: you can design and build the critical Fabric artifacts to prove patterns.
- Platform‑oriented: you think in reusable standards, templates, and repeatable governance.
- Strong consultative presence: you can advise product teams while also driving decisions and outcomes.
- Comfortable with authority: you can mandate standards when required to protect the platform and business.
- Documentation discipline: you produce clear ADRs, standards, and operating playbooks.
- Engagement & Collaboration
- Supports product teams through office hours and project-based sprints.
- Works primarily with: Azure lead architect, security architect/engineer, DevOps platform engineer, and product engineering teams.
- Data ownership remains with product teams; this role defines the how (standards/patterns/governance), not centralized ownership.
Requirements RequiredDeliverables
- Target-state architecture
- Data model standards: conceptual / logical / physical + templates
- Domain-oriented data product patterns and operating guidance
- Governance model: classification, retention, lineage, access controls
- Fabric workspace strategy + operating model (environments, isolation, ownership, lifecycle)
- CI/CD approach for Fabric artifacts integrated with platform guardrails
- IaC approach using Terraform for Fabric-related configuration and
- Cost model + capacity planning strategy (SKU sizing, isolation, show back/chargeback)
- Architecture Decision Records (ADRs) for key platform decisions
Qualifications
Required Experience & Skills
- 10+ years in data architecture/data engineering roles, including platform-scale design.
- Proven Microsoft Fabric production implementations you have delivered Fabric solutions that run in production with real operational constraints.
- Deep hands‑on expertise in Fabric areas central to our rollout:
- Data Engineering
- Data Factory (pipelines)
- Real‑time analytics / Event Streams
- Strong architecture capability across mixed data types: transactional, telemetry/events, documents, geospatial, time series.
- Demonstrated experience implementing and governing:
- Data modeling standards (conceptual/logical/physical)
- Data governance (classification, retention, lineage)
- Security patterns using Entra ID , RBAC, workspace‑level controls
- Compliance guardrails for GDPR, ISO 27001, and data residency
- Strong DevOps fluency:
- CI/CD patterns and operational delivery
- Terraform as mandatory IaC for repeatability and standardization
- Ability to define standards and enforce guardrails while maintaining a delivery‑first, pragmatic approach.
Preferred
- Experience supporting IoT and telemetry-heavy product ecosystems.
- Experience designing data quality frameworks and SLAs for operational analytics and near‑
- Familiarity integrating observability/security signals into Log Analytics and Sentinel.
Details
Originally posted on Himalayas
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