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 up-to-date 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.

📌 Azure Fabric Data Engineer (Chennai)
🏢 Relevantz Technology Services
📍 Chennai