Azure Data Warehouse Developer

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.

• 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 middleworkflows