Job Description: We are seeking an 5+ Years experienced Azure Data Warehouse Developer to join our growing data team. The ideal candidate will have a deep understanding of cloud-based data architecture, specifically within Microsoft Azure, and will play a key role in designing, implementing, and maintaining data warehouse solutions on Azure. You will collaborate with cross-functional teams to ensure scalable and high-performance data solutions. Roles & Responsibilities: • Designing and implementing dimensional models — star and snowflake schemas, slowly changing dimensions (SCD Types 1, 2, 3), and fact/dimension table strategies • Writing complex, optimized T-SQL including window functions, CTEs, dynamic SQL, and query tuning • Table design considerations within Fabric Warehouse: distribution strategies, indexing, partitioning, and statistics management • Data quality enforcement through constraints, validation logic, and reconciliation frameworks • Understanding of Fabric Warehouse's current limitations vs. Azure Synapse Dedicated SQL Pools, and how to work within them • Hands-on Synapse Analytics experience — dedicated/serverless SQL pools, distribution strategies • Deep ADLS Gen2 knowledge — hierarchical namespace, Parquet/Delta file formats, partitioning strategies • Storage security — RBAC, ACLs, managed identities, private endpoints • Managing large-scale file formats: Parquet, Delta, CSV, JSON, and Avro • Experience connecting to source systems: databases, REST APIs, flat files, SaaS platforms • Query and storage performance tuning — file size optimization, indexing, partitioning • Hands-on experience with Fabric's T-SQL Warehouse and understanding how it differs from Synapse • Knowledge of cross-database and cross-item queries spanning Lakehouse and Warehouse • Understanding of Fabric's V-Order optimization and Delta Lake file management • Identifying and resolving data skew, spill, and shuffle issues in Spark workloads • Monitoring capacity usage, query execution plans, and resource contention • Experience building semantic models directly on top of Fabric Warehouse or Lakehouse • Understanding of when to choose Fabric DW over Lakehouse SQL endpoint for a given workload • OneLake architecture — shortcuts to ADLS Gen2, Lakehouse vs. Warehouse trade-offs • Medallion architecture implementation (Bronze/Silver/Gold) • Lakehouse mirroring and real-time data ingestion patterns • Fabric Data Pipelines, Notebooks (PySpark/SQL), and Dataflows Gen2 • Delta Lake operations — OPTIMIZE, VACUUM, Z-ordering, time travel • Incremental load strategies: watermark patterns, change data capture (CDC), and merge/upsert logic • Implementing row-level security (RLS) and column-level security (CLS) in Fabric Warehouse • Managing workspace roles, item permissions, and One Lake access controls • Understanding of data lineage tracking and cataloging within Fabric • Compliance awareness: GDPR, HIPAA, or industry-specific data handling requirements Required Skills: • Direct Lake mode in Power BI and semantic model design • End-to-end security model spanning ADLS and Fabric • Row-level and column-level security in DW and semantic layers • Sensitivity labels and Microsoft Information Protection • Designing end-to-end solutions where ADLS underpins Fabric via One Lake shortcuts • ELT/ETL pattern selection and pipeline orchestration • Microsoft Purview for governance and lineage across ADLS and Fabric • Multi-workspace and multi-domain architecture patterns for enterprise environments • Disaster recovery, backup strategies, and SLA considerations within Fabric • Fabric REST APIs and CI/CD using Azure DevOps or GitHub • Comfortable with Fabric's rapid evolution and incomplete documentation • Experience with integrating with Human in the middle workflows