Azure Fabric Engineer / Architect

About the role

The role is part of a strategic initiative to consolidate and modernize the data platform using Microsoft Fabric and Azure-native services. The position requires a seasoned practitioner who can architect with confidence, build with precision, and enable the broader team through documentation, knowledge transfer, and technical leadership.

Responsibilities

• Data Platform Architecture & Design
• Design scalable, secure, and high-performing data platforms using Microsoft Fabric, Azure Data Services, Lakehouse, Warehouse, and OneLake.
• Define data architectures that support ingestion, transformation, storage, analytics, and operational reporting.
• Consolidate structured, semi-structured, and unstructured data from multiple source systems into a unified platform.
• Partner with business stakeholders, analysts, and engineering teams to translate requirements into practical technical solutions.
• ETL/ELT Engineering & Data Migration
• Design, develop, and maintain ETL/ELT pipelines for ingesting, transforming, and loading data into Microsoft Fabric and Azure environments.
• Lead or support data migration initiatives from legacy, on-premises, and third-party platforms into modern Azure/Fabric architectures.
• Perform source-to-target mapping, transformation logic development, reconciliation, and migration validation.
• Build repeatable ingestion patterns for databases, flat files, APIs, SaaS platforms, and cloud storage sources.
• Optimize pipelines for performance, reliability, scalability, and cost efficiency.
• DevOps / DataOps / Deployment Enablement
• Design and implement CI/CD pipelines for Fabric artifacts and supporting data workloads across dev, test, and production environments.
• Standardize deployment practices including environment parameterization, secret management, service principal-based deployments, and release controls.
• Support automation using Azure DevOps, Git-based workflows, YAML pipelines, and Fabric/API-based deployment methods.
• Establish deployment, rollback, and recovery procedures for production data solutions.
• Build orchestration and execution frameworks that support scheduling, dependency handling, retries, restartability, and backfills.
• Governance, Security & Operational Readiness
• Help define and implement governance controls including metadata, lineage, access control, auditability, and data quality validation.
• Implement monitoring and alerting for pipeline failures, data quality issues, and data freshness SLAs.
• Define and document operational procedures for incident response, reruns, escalation, and daily monitoring.
• Contribute to RTO/RPO planning, operational resilience, and production support readiness.
• Documentation, Collaboration & Leadership
• Produce and maintain architecture diagrams, technical documentation, runbooks, SOPs, and deployment guides.
• Conduct knowledge transfer and support operational enablement for engineering and support teams.
• Provide technical leadership and contribute best practices for Microsoft Fabric adoption and pipeline engineering.
• Mentor junior engineers and participate in design reviews, code reviews, and technical planning sessions.

Requirements

• 4+ years of experience in data engineering, data platform engineering, or cloud data solutions.
• Hands-on experience with Microsoft Fabric and core Azure data services.
• Strong experience building and supporting ETL/ELT pipelines and data migration solutions.
• Experience with Azure DevOps, Git workflows, CI/CD pipelines, and release management practices.
• Strong SQL skills and working knowledge of Spark, PySpark, or related data engineering tools.
• Experience with Lakehouse, Warehouse, Delta/Parquet-style processing, and cloud data storage concepts.
• Understanding of monitoring, orchestration, restartability, and production support requirements for data platforms.
• Experience with service principals, RBAC, secret management, and secure deployment practices.
• Strong documentation, troubleshooting, and cross-functional collaboration skills.

Skills

• Experience with Azure Synapse, Azure Data Factory, ADLS Gen2, and OneLake.
• Familiarity with Power BI semantic models, Direct Lake, and downstream analytics integration.
• Experience with data governance, lineage, metadata, and compliance-oriented data controls.
• Knowledge of Fabric REST APIs, automation frameworks, and enterprise scheduling tools.
• Experience defining operational standards, runbooks, and support models for enterprise data platforms.
• Microsoft Azure or Microsoft Fabric certifications.

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field — or equivalent practical experience.