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Brillio

Lead Data Engineer - R01558812

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Lead Data Engineer

Primary Skills

  • AKS, Event Hub, Azure DevOps, Cosmos DB, Azure Functions

    • Specialization

  • Azure Data Engineering Advanced: Senior Data Engineer

    • Job requirements

  • Job Description

    We are seeking a Senior Data Engineer with strong hands‑on expertise in Azure Data Platform and Microsoft Fabric to design, build, and scale modern, enterprise‑grade data solutions. The role involves working on end‑to‑end data engineering pipelines, lakehouse architectures, and analytics‑ready data models using Azure and Fabric’s unified analytics capabilities.

    Key Responsibilities

  • Design, develop, and manage end‑to‑end data pipelines using Microsoft Fabric (Data Pipelines, Lakehouse, Warehouse, OneLake) and Azure Data Factory
  • Build scalable data transformation and processing solutions using Fabric Notebooks, PySpark, Python, and SQL
  • Implement Lakehouse and Medallion Architecture (Bronze, Silver, Gold) to support analytics and reporting workloads
  • Develop and optimize SQL-based solutions including T‑SQL, stored procedures, and performance‑tuned queries
  • Integrate data from multiple sources including RDBMS, APIs, files, streaming sources, and cloud storage
  • Work with ADLS Gen2, Blob Storage, and OneLake for structured and unstructured data management
  • Enable analytics and reporting by integrating Fabric datasets with Power BI
  • Implement data quality checks, monitoring, logging, and error‑handling mechanisms
  • Support migration and modernization initiatives from ADF / Databricks to Microsoft Fabric, where applicable
  • Ensure adherence to data governance, security, lineage, and compliance standards (Microsoft Purview exposure preferred)
  • Collaborate closely with architects, analysts, and business stakeholders to translate requirements into scalable data solutions
  • Provide technical guidance and mentoring to junior engineers

    • Required Skills & Expertise

    Microsoft Azure & Fabric

  • Microsoft Fabric (Data Pipelines, Lakehouse, Warehouse, OneLake)
  • Azure Data Factory (ADF)
  • Azure Data Lake Storage Gen2 (ADLS G2)
  • Azure Blob Storage

    • Programming & Query Languages

  • SQL (Basic & Advanced)
  • T‑SQL
  • Stored Procedures
  • Python
  • PySpark / Spark SQL

    • Data Engineering & Architecture

  • ETL / ELT Fundamentals
  • Modern Data Platform Concepts
  • Data Warehousing & Lakehouse Architecture
  • Data Modeling Fundamentals (Star / Snowflake schemas)
  • Incremental loads, CDC, and watermarking techniques

    • Monitoring & Governance

  • Pipeline monitoring & performance optimization
  • Azure Monitoring / Fabric monitoring tools
  • Microsoft Purview (Data lineage & governance – good to have)

    • Good to Have

  • Experience with streaming or near real‑time processing
  • Exposure to Databricks in hybrid Azure–Fabric environments
  • CI/CD for data pipelines using Git / Azure DevOps
  • Experience supporting enterprise‑scale analytics platforms

    • Soft Skills

  • Strong problem‑solving and analytical mindset
  • Excellent communication and stakeholder management skills
  • Ability to work independently in fast‑paced delivery environments
  • Ownership mindset with focus on quality and reliability

    • Why Join Us

  • Work on cutting‑edge Azure & Microsoft Fabric implementations
  • Exposure to large‑scale enterprise modernization programs
  • Growth opportunities across cloud, data platforms, and analytics
  • Collaborative, high‑impact engineering culture

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