The Data Lead will architect build and optimize enterprise data warehousing and analytics solutions using Microsoft Fabric with deep expertise in data modeling pipeline engineering semantic modeling realtime data processing governance and analytics delivery. The role requires strong handson technical leadership and the ability to convert business requirements into scalable governed data solutions that drive measurable business outcomes. Engage with business stakeholders to understand analytical operational and compliance needs Convert business requirements into functional design sourcetotarget mappings transformation logic and technical specifications Validate requirements against enterprise data models and recommend architecture patterns Lakehouse Warehouse Realtime Hub Data Modeling Fabric Semantic Layer Design build and govern Fabric Semantic Models Direct Lake Import DQ Hybrid modes Define enterprisewide canonical models shared dimensions hierarchies KPIs and reusable DAX measures Optimize semantic models for performance using aggregations incremental refresh and partitioning strategies Enable certified datasets semantic governance and rolelevel security within Fabric ETLELT Engineering with Fabric Pipelines Dataflows Notebooks Build ingestion and transformation processes using Data Factory pipelines Dataflows Gen2 Warehouse pipelines and PySpark notebooks Maintain metadatadriven ETL patterns and reusable frameworks for ingestion harmonization and transformation Fabric Notebook Engineering Use Fabric Notebooks to perform PySpark transformations Delta Lake optimization Zorder vacuuming partitioning Data validation and data quality checks ML feature engineering and lightweight model operations Automate notebook execution via pipelines triggers and Fabric scheduling Integrate notebooks with Lakehouse tables Warehouse tables and ML model outputs Near RealTime NRT Data Processing in Fabric Design and implement nearrealtime data ingestion pipelines using Fabric RealTime Hub Event Streams KQL Databases Streaming Dataflows Build streaming transformations and realtime analytical models leveraging Kusto Query Language KQL and PySpark Structured Streaming Ensure lowlatency ingestion to LakehouseWarehouse for downstream consumption Optimize realtime workloads for durability recovery and performance under high throughput Build dashboards and semantic models that support nearrealtime refresh scenarios Performance Optimization Optimize SQL queries Lakehouse Delta tables semantic models DAX expressions and Power BI datasets Review and tune pipeline throughput notebook execution performance and refresh schedules Improve Direct Lake performance by optimizing storage layouts file size distributions and columns Perform workload monitoring using Fabric capacity metrics and logs Power BI Development Visualization Build highquality Power BI dashboards and enterprise reports integrated with centralized semantic models Develop DAX calculations KPIs UXUI standards drillthroughs and rowlevel security Drive semantic model reuse and promote governed gold datasets Governance Security Compliance Purview Integration Implement data governance and cataloging using Microsoft Purview for Fabric assets Manage lineage tracking glossary management classification and metadata enrichment Define enterprise security controls RBAC masking PII handling encryption retention policies Ensure compliance with GDPR CCPA HIPAA SOX and internal audit controls Govern Fabric workspace structure capacity usage data certification processes and lifecycle management Technical Leadership/ Program Delivery Lead data engineers BI developers and analysts across multiple initiatives Review designs STTMs code semantic models and performance benchmarks Own sprint planning estimation milestone tracking and stakeholder communication Promote documentation technical standards reusable design frameworks and automation Technical Expertise 8 years of data engineering or BI experience with 2 years in Microsoft Fabric Expert in data warehousing design dimensional modeling semantic modeling and data governance Strong handson experience with Fabric Lakehouses Warehouses Fabric Semantic Models Direct Lake Import Hybrid RealTime Hub Event Streams KQL Databases Notebooks PySpark data transformations optimization Data Factory pipelines Dataflows Gen2 Power BI modeling DAX report development Solid understanding of Delta Lake Spark performance tuning and workload optimization Expertise in implementing sourcetotarget mappings transformation logic and validation rules Preferred Skills Azure Synapse ADF ADLS Databricks experience Knowledge of DataOps