Microsoft Fabric SME

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Job Title: Microsoft Fabric SME
Location: Remote US and/OR LATAM
Job-Type: Contract
Role Overview:
Big O Tires is undertaking a foundational modernization of its Point of Sale (POS) data platform as part of the transition from Navex/DST to AutoLeap. At the same time, the organization is intentionally moving away from legacy on prem SQL Server–based data architectures (ICDB, DME/BOTCONDB) and establishing Microsoft Fabric as the primary analytics and data distribution platform. This initiative supports franchise sales and performance reporting, royalty-related sales calculation and reporting, customer and vehicle master data management, external integrations with SAP/CRM/credit card providers/third parties, and future migration of other operational data domains (inventory, warranty, orders, quantity on hand). Given the tight delivery timeline, breadth of downstream consumers, and early-stage Fabric maturity of the internal team, this role will lead the work end to end to ensure successful delivery with minimal rework and risk.
Responsibilities:

• Design end-to-end Fabric architecture, including ingestion from AutoLeap (Postgres / partner APIs), Bronze / Silver / Gold data layers, and lakehouse and semantic model strategy
• Establish standards for change data capture and incremental loading, global identifiers (customer, vehicle, store), and data quality, auditing, and reconciliation
• Oversee data pipelines (Fabric Pipelines / Notebooks), staging, transformations, and conformance
• Drive consolidation of ICDB and DME use cases into a single lakehouse
• Ensure outbound data feeds meet requirements for Power BI internal reporting, third-party partners (e.g., RRD), and internal consumers (Business Center, SAP, Oracle)
• Lead structured requirements intake with stakeholders and translate business needs into canonical POS data models and Gold-layer data products
• Validate mappings against AutoLeap source schemas
• Define and execute data completeness checks, reconciliation against legacy ICDB/DME outputs, and performance and refresh SLAs
• Develop formal test plans and acceptance criteria
• Cross-train internal analysts, engineers, and analytics leaders by pairing on design/builds, explaining architectural decisions, and documenting patterns and standards
• Leave behind repeatable frameworks, patterns, and standards

Requirements:

• Deep, hands-on experience with Microsoft Fabric, including Lakehouses, Fabric Pipelines, Notebooks (Spark/PySpark), and semantic models with Power BI integration
• Strong background in modern data architecture (lakehouse, medallion patterns)
• Proven experience leading system-of-record data migrations
• Experience with POS or transaction-heavy operational systems (retail, automotive, franchise, or similar)
• Experience with API and relational database ingestion (Postgres preferred)
• Experience designing data products for internal analytics and external data distribution (partners, vendors)
• Ability to lead ambiguity and define next steps independently
• Comfortable acting as architect, technical lead, and educator
• Strong communication skills with engineering teams, analytics consumers, and business stakeholders

 Job Title: Microsoft Fabric SME
Location: Remote US and/OR LATAM
Job-Type: Contract
Role Overview:
Our client is undertaking a foundational modernization of its Point of Sale (POS) data platform as part of the transition from Navex/DST to AutoLeap. At the same time, the organization is intentionally moving away from legacy on prem SQL Server–based data architectures (ICDB, DME/BOTCONDB) and establishing Microsoft Fabric as the primary analytics and data distribution platform. This initiative supports franchise sales and performance reporting, royalty-related sales calculation and reporting, customer and vehicle master data management, external integrations with SAP/CRM/credit card providers/third parties, and future migration of other operational data domains (inventory, warranty, orders, quantity on hand). Given the tight delivery timeline, breadth of downstream consumers, and early-stage Fabric maturity of the internal team, this role will lead the work end to end to ensure successful delivery with minimal rework and risk.
Responsibilities:

• Design end-to-end Fabric architecture, including ingestion from AutoLeap (Postgres / partner APIs), Bronze / Silver / Gold data layers, and lakehouse and semantic model strategy
• Establish standards for change data capture and incremental loading, global identifiers (customer, vehicle, store), and data quality, auditing, and reconciliation
• Oversee data pipelines (Fabric Pipelines / Notebooks), staging, transformations, and conformance
• Drive consolidation of ICDB and DME use cases into a single lakehouse
• Ensure outbound data feeds meet requirements for Power BI internal reporting, third-party partners (e.g., RRD), and internal consumers (Business Center, SAP, Oracle)
• Lead structured requirements intake with stakeholders and translate business needs into canonical POS data models and Gold-layer data products
• Validate mappings against AutoLeap source schemas
• Define and execute data completeness checks, reconciliation against legacy ICDB/DME outputs, and performance and refresh SLAs
• Develop formal test plans and acceptance criteria
• Cross-train internal analysts, engineers, and analytics leaders by pairing on design/builds, explaining architectural decisions, and documenting patterns and standards
• Leave behind repeatable frameworks, patterns, and standards

Requirements:

• Deep, hands-on experience with Microsoft Fabric, including Lakehouses, Fabric Pipelines, Notebooks (Spark/PySpark), and semantic models with Power BI integration
• Strong background in modern data architecture (lakehouse, medallion patterns)
• Proven experience leading system-of-record data migrations
• Experience with POS or transaction-heavy operational systems (retail, automotive, franchise, or similar)
• Experience with API and relational database ingestion (Postgres preferred)
• Experience designing data products for internal analytics and external data distribution (partners, vendors)
• Ability to lead ambiguity and define next steps independently
• Comfortable acting as architect, technical lead, and educator
• Strong communication skills with engineering teams, analytics consumers, and business stakeholders

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