Fabric Data Engineer/Lead for Arlington, VA (Priority 1) and St. Louis, MO (Priority 2)Experience

Fabric Data Engineer/Lead (Day1 Onsite) Arlington, VA (Priority 1) and St. Louis, MO (Priority 2)Experience • 12+ years in Data Architecture / Analytics Platforms / Cloud Data Engineering • 2–4+ 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 Key Responsibilities (Must-Have) • 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 Behavioral Competencies • 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) Thanks &Regards Rahul Sharma | Team Lead Amaze Systems Inc E: |