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Consulting Senior Data Architect (Microsoft Fabric Focus)

Roles & Responsibilities

  • 10+ years in data architecture/data engineering roles, including platform-scale design
  • Proven Microsoft Fabric production implementations delivering Fabric solutions in production with real operational constraints
  • Deep hands-on expertise in Fabric areas including Data Engineering (Data Factory pipelines) and real-time analytics/event streams
  • Strong DevOps fluency with CI/CD patterns and Terraform IaC for Fabric configuration

Requirements:

  • Architect and implement Fabric-based data platform solutions (data engineering pipelines, real-time analytics, and event streams) with hands-on delivery and standardization
  • Build and standardize Fabric patterns for ingestion, transformation, and serving; create repeatable reference implementations for common product scenarios
  • Define target-state Fabric architecture, data modeling standards (conceptual/logical/physical), governance, security, and CI/CD/IaC for Fabric artifacts
  • Establish capacity planning, cost model, and operational readiness including reliability, observability, governance forums, and cross-team collaboration with platform engineering

Job description

PLEASE NOTE:

  • It is a 100% Remote position in Canada.
  • Candidates Preferred from EST/CST Time Zone.

Key Responsibilities:

Microsoft Fabric Enablement (Hands-on Delivery + 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 (Target State + 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 by Design

  • 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) for Fabric

  • 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, and Chargeback/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 Operational Readiness

  • 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

Required Deliverables:

You will be accountable for producing the following:

  • 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-real-time processing.
  • Familiarity integrating observability/security signals into Log Analytics and Sentinel.


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