Data Engineer-Data Platforms-Azure

Introduction

A career in IBM Consulting is grounded in enduring client relationships and hands-on collaboration across the globe. You’ll partner with leading organizations in multiple industries, supporting their hybrid cloud and AI transformation initiatives. Backed by strategic partners, IBM technology, and Red Hat, you’ll gain the capabilities to help clients drive meaningful outcomes and strengthen real-world impact. At IBM Consulting, curiosity is a key driver of success. You’ll be encouraged to question convention, investigate new approaches, and deliver inventive solutions that produce measurable results. Our growth- and empathy-oriented culture supports your long-term career development while recognizing and valuing your individual skills and experiences.

Your Role And Responsibilities

As a Data Engineer specializing in Data Platforms on Azure, you will consult on, design, build, and manage data engineering solutions across the Azure Cloud ecosystem. You’ll create, implement, and support both batch and real-time data pipelines using a range of Azure services.

Your Primary Responsibilities Will Include

• Design and Build Data Pipelines: Plan, develop, and run batch and real-time data pipelines using Azure services including Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub.
• Develop Data Layer: Design, build, and maintain the data layer using Azure Synapse Analytics, SQL DW, and Cosmos DB.
• Implement Azure Data Platform: Implement and support Azure Data Platform capabilities, including ADLS2, Blob Storage, SQLDW, Synapse Analytics (Spark and SQL), Azure Functions with Python, Azure Purview, and Cosmos DB.
• Utilize Open Source Technologies: Leverage open source tools such as Apache Airflow and dbt, along with Spark / Python or Spark / Scala, to enable and enhance data engineering solutions.
• Ensure Seamless Operations: Operate and maintain data engineering solutions to ensure reliable batch and real-time data processing.
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Exposure to Azure Toolset: Demonstrated proficiency in Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub for designing, building, and operating batch and real-time data pipelines.
• Data Engineering on Azure: Experience with Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB.
• Open Source Technologies: Exposure to open source technologies such as Apache Airflow and dbt, Spark / Python, or Spark / Scala to support data engineering solutions.
• Data Pipeline Development: Experience developing and maintaining data engineering solutions on the Azure Cloud ecosystem, including designing, building, and operating batch and real-time data pipelines.
• Azure Data Layer Design: Experience designing, building, and operating the data layer on Azure Synapse Analytics, SQL DW, and Cosmos DB.
  
  

Preferred Technical And Professional Experience

• Proficiency in Azure Services: Exposure to Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub to design, build, and operate batch and real-time data pipelines.
• Open Source Technologies: Exposure to open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala to support data engineering solutions.
• Data Engineering on Azure: Experience working with Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB.