About this role

Microsoft Fabric Data Engineer role focused on designing, building, and operating modern data platforms using Microsoft Fabric, including ingestion, modeling, serving, governance, performance, DevOps, and collaboration with analytics and BI stakeholders.

Responsibilities

• Build and manage Lakehouses (Delta Lake) and Fabric Data Warehouses.
• Develop Data Pipelines and Dataflows Gen2 for batch and near-real-time ingestion.
• Create and optimize Notebook-based transformations (PySpark/SQL) and SQL stored procedures for DW workloads.
• Implement medallion architecture (bronze/silver/gold) for scalable curation.
• Publish certified semantic models and Power BI datasets aligned to business domains.
• Optimize storage/compute in OneLake (file formats, partitioning, z-ordering).
• Tune Spark and SQL workloads (caching strategies, concurrency, workload isolation).
• Implement robust retry, alerting, and monitoring (Fabric Monitoring Hub, Metrics app).
• Conduct end-to-end pipeline performance testing and scalability assessments.
• Enforce data governance with sensitivity labels, row-level/column-level security, and workspace roles.
• Manage item-level permissions and Managed Identities for sources.
• Apply data quality rules, lineage, and documentation.
• Ensure compliance with organizational standards including PII handling, audit, and retention.
• Use Fabric Git integration and Deployment Pipelines for CI/CD across dev/test/prod.
• Parameterize pipelines and environments; externalize configuration and secrets.
• Implement automated testing for data transformations and schemas.
• Drive release management, change control, and rollback strategies.
• Partner with analytics engineers and BI teams to design star schemas, semantic models, and DAX measures.
• Work with data source owners for SLAs, schema change management, and contracts.
• Translate business requirements into technical designs and document architecture decisions.
• Provide knowledge transfer, best practices, and support to data consumers.

Required qualifications

• Hands-on experience with Microsoft Fabric.
• Experience with OneLake, Lakehouse (Delta), Fabric Data Warehouse, Data Pipelines, Dataflows Gen2, Notebooks, Semantic Models/Power BI, and Monitoring Hub.
• Experience with PySpark, SQL (T-SQL), and Delta Lake operations.
• Familiarity with DAX.
• Experience with dimensional modeling, Data Vault or medallion patterns, and data quality frameworks.
• Experience with partitioning, file formats (Parquet/Delta), caching/z-ordering, job orchestration, and monitoring.
• Experience with Git, Fabric Deployment Pipelines, YAML CI/CD, and IaC exposure.
• Experience with RLS/CLS, sensitivity labels, access patterns, audit/logging, and lineage.

Preferred qualifications

• Experience with Power BI modeling including star schemas, relationships, calculation groups, and DAX.
• Exposure to streaming/real-time technologies such as Eventstream, Real-Time Hub, and KQL databases.
• Experience integrating with external sources such as SQL Server, SAP, Dataverse, and REST APIs.
• Familiarity with Microsoft Purview for governance and lineage.
• DP-600 certification strongly preferred.
• DP-203 certification nice to have.