Data Engineer – Azure Fabric Engineer Consultant

Job Description: You’ll lead client discovery to understand business goals, data landscape, constraints, and success metrics—then translate findings into a clear delivery plan. You’ll design and recommend data lake, Lakehouse, data warehouse, and analytical data store architectures on Azure and Microsoft Fabric aligned to client needs. You’ll implement (and/or guide implementation of) ingestion, transformation, and orchestration pipelines using Microsoft Fabric experiences and Azure services (e.g., Data Factory, Synapse, Databricks). You’ll integrate data from operational systems, APIs, and third-party sources and transform raw data into curated datasets ready for consumption. You’ll build and maintain analytics-ready data models and schemas; implement enrichment, business rules, and reusable patterns for consistency across projects. You’ll enable multiple compute engines (SQL, Spark/PySpark, Spark SQL, KQL) to run against shared datasets, supporting diverse analytics scenarios. You’ll design and build AI-enabled analytics and data products, including agentic workflows (e.g., retrieval-augmented generation patterns), ensuring solutions are scalable, secure, and aligned with responsible AI practices. You’ll establish data quality practices (validation, reconciliation, testing) and monitoring, troubleshoot failures, and continuously improve pipeline resiliency. You’ll optimize transformations, query performance, and pipeline execution to meet client SLAs and cost objectives. You’ll implement logging, metrics, and operational runbooks, and support deployments, cutovers, and hypercare as needed. You’ll design and implement security, governance, and compliance controls (access, least privilege, data protection, lineage) across Azure and Fabric. You’ll facilitate workshops and communicate architecture tradeoffs, partnering with client stakeholders, architects, analysts, and BI developers to deliver trusted datasets. You’ll produce clear consulting deliverables (design docs, diagrams, implementation guides) and enablement materials to support adoption and smooth handoff. Requirements: Experience designing and delivering modern analytics platforms (Lakehouse and/or data warehouse patterns) on Azure and/or Microsoft Fabric, including client-facing delivery. Strong SQL skills with experience building transformations and dimensional/analytical models. Hands-on experience with Spark (PySpark/Spark SQL) and/or KQL for data engineering and analytics workloads. AI development experience, including designing agentic solutions (multi-step/tool-using workflows) that leverage enterprise data (e.g., retrieval-augmented generation patterns). Experience building reliable data pipelines, including orchestration, scheduling, error handling, and automated monitoring. Knowledge of data quality practices (validation, reconciliation, testing) and incident triage/root-cause analysis. Working knowledge of Power BI (including semantic modeling concepts) to support end-to-end analytics delivery; Power Apps experience is a plus. Understanding of security and governance concepts for data platforms (access controls, least privilege, compliance, lineage). Strong communication skills, with the ability to present recommendations, align stakeholders, and manage expectations in a client environment.

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