Azure Fabric Data Engineer

Role Overview

We are seeking an experienced Azure Fabric Data Engineer to define, design, and govern enterprise-scale data platforms using Microsoft Fabric. This role goes beyond engineering execution and focuses on end-to-end architecture, platform strategy, and governance, ensuring scalable, secure, and high-performing data ecosystems.

Key Responsibilities

Data Architecture & Platform Strategy

• Define and implement enterprise data architecture leveraging Microsoft Fabric (Lakehouse, Data Warehouse, Data Factory, Real-Time Analytics).

• Design modern data platform strategies including Medallion architecture (Bronze, Silver, Gold).

• Architect scalable Lakehouse and Delta Lake solutions for unified storage and processing.

• Establish data integration patterns for batch, micro-batch, and real-time ingestion.

• Lead platform selection, design standards, and reference architectures.

Solution Design & Engineering Oversight

• Provide architectural guidance for ETL/ELT pipelines using Fabric Data Factory and Spark.

• Oversee development of PySpark, SQL, and notebook-based data solutions.

• Define best practices for data modeling (Star schema, Data Vault, dimensional modeling).

• Ensure alignment between data engineering, BI, and AI/ML workloads. • Review and approve solution designs to ensure adherence to enterprise standards. Governance, Security & Compliance

• Define and enforce data governance frameworks, including data lineage, cataloging, and metadata management.

• Implement data security architectures (RBAC, data masking, encryption, access controls).

• Ensure compliance with organizational policies and regulatory requirements.

• Establish data quality, validation, and observability frameworks.

• Drive cost governance and FinOps practices for Fabric environments.

Performance & Optimization

• Architect solutions for high performance and scalability across large datasets.

• Establish standards for query optimization, partitioning, and indexing strategies.

• Design cost-efficient architectures using Fabric capacity and workload optimization techniques.

• Monitor and optimize platform performance across storage, compute, and pipelines.

Leadership & Stakeholder Engagement

• Act as a trusted advisor to business and technology leaders on data strategy.

• Lead and mentor data engineers, leads, and solution architects.

• Facilitate architecture reviews, design discussions, and governance boards.

• Translate business goals into scalable and actionable technical architectures.

• Drive adoption of Fabric and modern data practices across the organization.

Innovation & Continuous Improvement

• Stay current with Microsoft Fabric roadmap and emerging technologies.

• Introduce innovations in real-time analytics, AI integration, and unified analytics platforms.

• Drive continuous improvement in architecture patterns, tooling, and frameworks.

• Define reusable components, accelerators, and templates. Required

Skills & Qualifications

Technical Expertise

• Strong experience with Microsoft Fabric components (Lakehouse, Data Factory, Power BI, Real-Time Analytics).

• Deep expertise in big data processing (Spark/PySpark).

• Advanced knowledge of data modeling techniques (Dimensional, Data Vault, Medallion).

• Proficiency in SQL, distributed data systems, and data orchestration frameworks.

• Experience with Delta Lake and modern data lake architectures.