Fabric Data Engineer / Azure Data Engineer

  • Location: No Location Set
  • Type: Contract
  • Job #35270
  • Hands-on Data Engineer with strong Microsoft Fabric experience, including Lakehouse, OneLake, Data Factory/Pipelines, Warehousing, and Fabric ecosystem services.
  • Strong Python development skills for data engineering, data transformation, automation, and pipeline development.
  • Design, build, and support scalable ETL/ELT data pipelines across enterprise Azure environments.
  • Experience working with Microsoft Fabric Lakehouse architecture, including data ingestion, transformation, storage, and analytics enablement.
  • Strong understanding of data engineering fundamentals, including data modeling, partitioning, optimization, and performance tuning.
  • Experience supporting Azure Data Platform technologies, including Azure Data Factory, Azure Synapse Analytics, Azure Storage, and related services.
  • Ability to work within large-scale enterprise data environments supporting multiple business units and data domains.
  • Knowledge of Medallion Architecture (Bronze, Silver, Gold) and practical implementation of modern data lakehouse solutions.
  • Experience integrating and transforming structured and semi-structured data sources including APIs, databases, JSON, CSV, and cloud-based systems.
  • Understanding of Fabric operational monitoring, capacity consumption monitoring, and platform governance best practices.
  • Ability to clearly explain and demonstrate the distinction between Fabric Files, Tables, Lakehouses, Warehouses, and OneLake storage concepts.
  • Exposure to Azure DevOps and CI/CD practices, including deployment automation, source control, release management, and pipeline promotion across environments.
  • Experience supporting cloud data modernization, migration, and analytics initiatives within Azure-centric ecosystems.
  • Strong SQL skills including complex joins, performance optimization, data validation, troubleshooting, and query development.
  • Exposure to Databricks, Spark, or PySpark is beneficial but not considered the primary requirement.
  • Experience with Real-Time Analytics and KQL (Kusto Query Language) is considered a strong asset.
  • Previous experience working within regulated enterprise environments such as financial services, insurance, healthcare, government, or large corporate organizations is highly desirable.
  • Ability to support integration across multiple systems, applications, databases, and cloud platforms.
  • Strong communication skills with the ability to interact effectively with technical teams, business stakeholders, and client-facing delivery groups.
  • Self-starter capable of working independently with minimal supervision while contributing effectively within collaborative project teams.
  • Demonstrated “get it done” attitude with a reputation for ownership, accountability, reliability, and delivering results.
  • Motivated consultant who learns quickly, asks intelligent questions, and can become productive rapidly within a complex client environment.
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