Data Warehouse Architect

The Data Warehouse Architect is responsible for designing, governing, and evolving the enterprise data warehouse architecture in Microsoft Fabric. This role provides hands-on technical leadership for a metadata-driven, layered data platform spanning Bronze, Silver, and Gold data products and supports analytics and Power BI consumption.

The architect will establish scalable patterns for ingestion, transformation, dimensional modeling, orchestration, deployment, security, data quality, lineage, monitoring, and operational support. The role works closely with data engineering, business intelligence, enterprise applications, infrastructure/security, and business stakeholders and is expected to provide architecture guidance as well as contribute directly to implementation.

Pay: $130,000 / year, * Architect the Microsoft Fabric data warehouse and lakehouse environment, including workspace, capacity, data domain, medallion-layer, and data product design patterns.

• Design enterprise data models for analytical workloads, including dimensional/star schemas, conformed dimensions, facts, semantic-ready structures, historical tracking, and appropriate data-grain standards.
• Define and enforce Bronze, Silver, and Gold architecture standards, including naming, lineage, audit fields, batch/run metadata, reconciliation, dependency handling, restartability, exception handling, and retention.
• Design and guide metadata-driven ingestion and transformation frameworks using Fabric Data Factory pipelines, notebooks, SQL, OneLake, Lakehouse, and Warehouse capabilities as appropriate.
• Establish patterns for integrating enterprise systems such as Workday, Salesforce/Bullhorn, operational databases, APIs, flat files, and other internal or external data sources.
• Create architecture standards for data quality, observability, reconciliation, logging, monitoring, alerting, operational support, and production troubleshooting.
• Partner with Power BI developers to ensure warehouse and semantic-layer designs support performant, governed reporting and analytics.
• Own source-to-target architecture, logical and physical data models, interface specifications, data dictionaries, lineage documentation, architecture decision records, and technical design documentation.
• Define security patterns for workspaces, data access, service principals/managed identities where applicable, least-privilege access, and appropriate separation of development, test, and production environments.
• Lead Azure DevOps (ADO) practices for data-platform delivery, including Git repositories, branching strategy, pull requests, work items, backlog traceability, CI/CD pipelines, release controls, and promotion across environments.
• Conduct architecture and code/design reviews, mentor data engineers and BI developers, and help establish reusable development standards and engineering guardrails.
• Evaluate performance, scalability, reliability, and cost considerations and recommend improvements to Fabric workloads and data-platform architecture.
• Collaborate with application owners, security, governance, and business teams to translate data requirements into sustainable enterprise data solutions.
• Support incident root-cause analysis and remediation for complex data warehouse, pipeline, integration, and deployment issues., This position is not expected to have direct supervisory responsibility initially. The role will provide technical leadership, architecture direction, design review, and mentoring to data engineering and business intelligence resources., Work is primarily performed in a professional office or remote environment using standard computer, collaboration, and communications equipment. The position requires extended periods of computer-based technical work and participation in virtual and in-person meetings as business needs require.

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Engineering, Mathematics, or a related technical field, or equivalent combination of education and relevant experience.

Extensive experience designing and delivering enterprise data warehouses, modern analytics platforms, or lakehouse architectures.

Hands-on experience with Microsoft Fabric and strong SQL-based data warehouse design and development experience.

Experience with enterprise data integration, orchestration, data modeling, data quality, and production support., * 7+ years of progressive experience in data architecture, data engineering, data warehousing, or business intelligence, with experience serving as a technical architect or senior technical lead.

• Strong hands-on knowledge of Microsoft Fabric, including OneLake, Lakehouse, Warehouse, Data Factory pipelines, notebooks, SQL endpoints, and integration with Power BI.
• Strong Azure DevOps (ADO) experience, including Boards, Repos/Git, pull requests, branching, CI/CD, release management, and deployment governance.
• Advanced SQL and data-modeling expertise, including dimensional modeling, slowly changing dimensions, surrogate keys, historization, incremental processing, and reconciliation patterns.
• Experience designing metadata-driven data pipelines and reusable ingestion/orchestration frameworks.
• Experience with REST APIs, JSON, files, relational sources, SaaS platforms, and enterprise application integration.
• Experience with Power BI semantic models and understanding how warehouse design affects model performance and reporting usability.
• Experience with data governance, security, lineage, data quality, monitoring, and DevOps practices for enterprise data platforms.
• Microsoft Fabric, Azure Data Engineer, Power BI, or related Microsoft certifications are preferred but not required., * Knowledge of modern enterprise data architecture, data warehousing, lakehouse patterns, dimensional modeling, data governance, data security, and analytics architecture.
• Skill in Microsoft Fabric, T-SQL/SQL, data modeling, ETL/ELT design, orchestration, Azure DevOps, Git, CI/CD, technical documentation, and architecture diagramming.
• Ability to move between architecture and hands-on implementation, diagnose complex data issues, establish practical standards, and simplify technical designs for delivery teams.
• Ability to communicate architecture decisions, risks, tradeoffs, dependencies, and implementation guidance to technical teams, business stakeholders, and leadership.
• Ability to mentor engineers, review technical work, promote consistent engineering practices, and drive solutions from design through production support., The employee must be able to perform the essential functions of the position with or without reasonable accommodation. The role generally requires the ability to remain in a stationary position for extended periods, operate a computer and standard office equipment, communicate effectively in meetings, and occasionally move or transport typical office materials.