We are seeking an experienced Azure Fabric Engineer to design, build, and operationalize modern data solutions across Microsoft Fabric and Azure. This role will bridge data architecture, ETL/ELT pipeline development, data migration, and DevOps/DataOps practices to create scalable, secure, and production-ready data platforms.
The ideal candidate understands how to architect a governed data environment while also being hands-on in building pipelines, supporting deployments, integrating disparate source systems, and improving operational reliability across development, test, and production environments.
Key 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 systems into a unified data platform.
- Partner with business stakeholders, analysts, engineers, and technical teams to translate business 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-based 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
- release controls and approval workflows
- 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.
- Support compliance and security best practices aligned to organizational and regulatory requirements.
- Implement monitoring and alerting for pipeline failures, data quality issues, and data freshness SLAs.
- Define and document operational procedures for incident response, reruns, escalation, support, 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, pipeline engineering, and deployment standards.
- Mentor junior engineers and participate in design reviews, code reviews, and technical planning sessions.
Required Qualifications
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field, or equivalent practical experience.
- 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.
Preferred Qualifications
- 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.
Core Technical Skills
- Microsoft Fabric
- Azure DevOps
- Azure Data Factory
- Azure Synapse
- Lakehouse / Warehouse
- OneLake / ADLS Gen2
- SQL
- Spark / PySpark
- ETL / ELT
- Data Migration
- CI/CD and Release Management
- DataOps / Orchestration
- REST API Automation
- RBAC / Entra ID / Key Vault
Ideal Profile
This role is ideal for someone who can operate between solution architecture and hands-on engineering. The right candidate is comfortable designing the bigger picture, but also enjoys building pipelines, solving deployment challenges, improving operational maturity, and making data platforms production-ready.