Business Intelligence Architect

Summary

Position: Business Intelligence Architect

Overview

The Business Intelligence Architect owns the data foundation that sits between our source systems and the reports consumed by the business. This role designs and builds the transformation layer on top of our Azure Synapse and SQL infrastructure — creating clean, governed, and consistent data models that enable reliable reporting across all business functions.

Key Aspects of the role include:

• Building and maintaining the layered data architecture that transforms raw ERP tables into stable, business-ready models.
• Serving as the technical link between IT infrastructure and business-facing analytics.
• Translating business reporting requirements into data structures that support accurate, consistent decision-making.

Responsibilities

• Assess, document, and extend the existing Synapse and SQL data environment — identify what is salvageable and what needs to be rebuilt.
• Design and implement a layered data architecture (Bronze/Silver/Gold) that ingests raw source tables and produces clean, queryable views for downstream reporting.
• Build dimensional models and star schemas across key business domains including sales, inventory, production, purchasing, and finance.
• Define transformation logic, business rules, and grain definitions so all reports draw from a consistent version of truth.
• Own data pipeline health — refresh schedules, incremental load logic, and failure alerting.
• Optimize query performance across the transformation layer including indexing, materialization, and incremental refresh policies.
• Partner with IT on the underlying Azure Synapse and SQL infrastructure and build the technical case for platform improvements including Microsoft Fabric migration.
• Develop and maintain Power BI semantic models and core reports on top of the governed data layer.
• Write and optimize DAX measures and calculated columns to support operational and executive reporting.
• Publish curated, documented datasets that enable business users to answer ad-hoc questions without individual report requests.
• Enforce naming conventions, lineage documentation, and data governance standards across the analytics environment.
• Manage workspace permissions and row-level security to ensure appropriate data access.

Qualifications

• 3+ years of experience in data engineering, data architecture, or a combined BI/data modeling role — manufacturing or ERP environment preferred.
• Strong SQL proficiency and hands-on experience with Azure Synapse Analytics, Azure Data Factory, or equivalent cloud data platforms.
• Demonstrated experience designing dimensional models, star schemas, and layered/medallion data architectures.
• Power BI proficiency including semantic model development and DAX — sufficient to validate and deliver reports from the data layer.
• Familiarity with Microsoft Dynamics 365 or other enterprise ERP data structures.
• Ability to assess an existing data environment, identify technical debt, and build a practical remediation plan.
• Clear communicator — able to explain technical decisions to non-technical stakeholders.
• Comfortable operating independently in a lean, fast-moving team environment.

Job Description

Position: Business Intelligence Architect

Overview

The Business Intelligence Architect owns the data foundation that sits between our source systems and the reports consumed by the business. This role designs and builds the transformation layer on top of our Azure Synapse and SQL infrastructure — creating clean, governed, and consistent data models that enable reliable reporting across all business functions.

Key Aspects of the role include:

• Building and maintaining the layered data architecture that transforms raw ERP tables into stable, business-ready models.
• Serving as the technical link between IT infrastructure and business-facing analytics.
• Translating business reporting requirements into data structures that support accurate, consistent decision-making.

Responsibilities

• Assess, document, and extend the existing Synapse and SQL data environment — identify what is salvageable and what needs to be rebuilt.
• Design and implement a layered data architecture (Bronze/Silver/Gold) that ingests raw source tables and produces clean, queryable views for downstream reporting.
• Build dimensional models and star schemas across key business domains including sales, inventory, production, purchasing, and finance.
• Define transformation logic, business rules, and grain definitions so all reports draw from a consistent version of truth.
• Own data pipeline health — refresh schedules, incremental load logic, and failure alerting.
• Optimize query performance across the transformation layer including indexing, materialization, and incremental refresh policies.
• Partner with IT on the underlying Azure Synapse and SQL infrastructure and build the technical case for platform improvements including Microsoft Fabric migration.
• Develop and maintain Power BI semantic models and core reports on top of the governed data layer.
• Write and optimize DAX measures and calculated columns to support operational and executive reporting.
• Publish curated, documented datasets that enable business users to answer ad-hoc questions without individual report requests.
• Enforce naming conventions, lineage documentation, and data governance standards across the analytics environment.
• Manage workspace permissions and row-level security to ensure appropriate data access.

Qualifications

• 3+ years of experience in data engineering, data architecture, or a combined BI/data modeling role — manufacturing or ERP environment preferred.
• Strong SQL proficiency and hands-on experience with Azure Synapse Analytics, Azure Data Factory, or equivalent cloud data platforms.
• Demonstrated experience designing dimensional models, star schemas, and layered/medallion data architectures.
• Power BI proficiency including semantic model development and DAX — sufficient to validate and deliver reports from the data layer.
• Familiarity with Microsoft Dynamics 365 or other enterprise ERP data structures.
• Ability to assess an existing data environment, identify technical debt, and build a practical remediation plan.
• Clear communicator — able to explain technical decisions to non-technical stakeholders.
• Comfortable operating independently in a lean, fast-moving team environment.