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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Lead/Architect with Microsoft Fabric / Power BI / Synapse - **Company:** Code - **Location:** Arlington, VA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Query Performance, Business Analytics Applications, Computing Platforms, Cloud Database, Continuous Integration, Data Architecture, Data Mart, DevOps, Dimensional Modeling, Python (Programming Language), Metadata, Windows PowerShell, Role-Based Access Control, Power BI, Azure Active Directory, Scripting, Azure Data Factory, Microsoft Fabric, Git Flow, Data Lineage, Restful APIs - **Published:** May 16, 2026 - **Apply:** https://www.dice.com/job-detail/14273a80-7ae0-41a1-8474-5f800704db36 ## About the Role * 12+ years in Data Architecture / Analytics Platforms / Cloud Data Engineering * 4+ years in Microsoft analytics ecosystem (Fabric / Power BI / Synapse / Azure Data) * Proven experience designing platforms for large enterprises (multi-team, multi-domain, 1k+ users) * Experience implementing governance and security at scale, * Strong architectural thinking with a platform engineering mindset * Excellent stakeholder management and communication (technical + executive) * Ability to define standards and drive adoption across teams * Pragmatic approach balances governance with agility and self-service * Strong documentation discipline (blueprints, playbooks, reference patterns) ## Description Job Title: Data Lead/Architect with Microsoft Fabric / Power BI / Synapse Location: Arlington, VA (Priority 1) and St. Louis, MO (Priority 2) - ONSITE Duration: Contract, * Fabric Platform Design & Workspace Architecture: Design scalable workspace and capacity strategy: * Domain-aligned and environment-separated structure (dev/test/prod) * Naming conventions, tagging/taxonomy, ownership model Design OneLake organization: * Folder conventions, zones (landing/curated/serving), lifecycle conventions * Standards for Delta table structure, partitioning, retention, and schema evolution Define item and data product blueprints: * When to use Lakehouse vs Warehouse vs Real-time capabilities * How to structure pipelines, notebooks, dataflows, and semantic models Define and implement architecture patterns: * Medallion architecture standards and curated modeling approach * Dimensional modeling strategy for data marts * Semantic model standards for reuse, performance, and governance Security & identity Setup: * Microsoft Entra ID group-based RBAC * Least privilege patterns, separation of duties * RLS/OLS patterns in semantic models Design and Setup Governance, including but not limited to: * Apply Fabric-native governance best practices: * Workspace roles and permission bundles for personas * Controlled sharing patterns to reduce data sprawl * Standards for certification/endorsement process Work with governance teams to ensure: * Metadata capture conventions are consistently applied * Data Lineage is captured * Sensitivity labeling strategy is embedded in workflows Build Frameworks around DevOps & Automation: * CI/CD (Git workflows, release/promotion strategies) * Scripting/automation mindset (PowerShell/Python preferred; REST APIs) * Monitoring, Observability & Operational Readiness: Design and implement monitoring for: * Pipelines, notebooks, dataflows execution success and runtimes * Warehouse/Lakehouse query performance and refresh health * Semantic model refresh and usage trends * Capacity utilization and throttling patterns * Define alerting thresholds, incident classification, and runbooks * Drive operational readiness gates before production cutovers Cost Optimization: * Implement design-time and run-time cost optimization: * Scheduling and workload shaping to reduce peak contention * Reuse strategies (shared curated layers, shared semantic models) * Identify duplication and encourage governed reuse (OneLake alignment) Provide capacity strategy inputs: * Right-sizing, workload isolation guidance for critical workloads * Cost allocation approach by workspace/domain where feasible Enablement, Standards, and Collaboration with Delivery Teams Define golden path patterns and accelerate delivery: * Templates and standards for pipelines and lakehouse layout * PR review checklists for Fabric engineering deliverables Provide architecture oversight during implementation: * Design reviews, technical governance checkpoints, risk mitigation Coach teams on best practices: * Performance, security, operational readiness, and governance adoption ## Related Videos - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Dev Digest 139 - Soft and hard queries](https://www.wearedevelopers.com/magazine/487-dev-digest-139-soft-and-hard-queries)