Data Engineer-Data Platforms-Azure

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

As a Data Engineer specializing in Data Platforms on Azure, you will advise on, develop, and maintain data engineering solutions on the Azure Cloud ecosystem. You will design, build, and operate batch and real-time data pipelines using various Azure services.

Your Primary Responsibilities Will Include

• Design and Build Data Pipelines: Design, build, and operate batch and real-time data pipelines using Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub.
• Develop Data Layer: Design, build, and operate the data layer on Azure Synapse Analytics, SQL DW, and Cosmos DB, ensuring seamless data integration and management.
• Leverage Azure Data Platform: Utilize Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB, to develop and maintain scalable data solutions.
• Implement Open Source Technologies: Apply expertise in open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala to enhance data engineering solutions.
• Ensure Data Quality: Collaborate to ensure high-quality data delivery, adhering to data governance and compliance standards.
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Azure Data Engineering Expertise: Experience with designing, building, and operating batch and real-time data pipelines using Azure services such as Azure Synapse Analytics, Azure Data Factory, Azure DataBricks, and Event Hub.
• Data Layer Development: Experience in designing, building, and operating the data layer on Azure Synapse Analytics, SQL DW, and Cosmos DB, ensuring seamless data integration and management.
• Azure Data Platform Proficiency: 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: Experience with open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala in data engineering solutions.
• Data Quality Assurance: Experience in ensuring high-quality data delivery, adhering to data governance and compliance standards in a cloud-based data engineering environment.
  
  

Preferred Technical And Professional Experience

• Proficiency in Apache Kafka: Experience with Managed Streaming for Apache Kafka is beneficial for enhancing real-time data pipeline capabilities.
• Knowledge of Azure Functions: Familiarity with Azure functions with Python is advantageous for developing scalable data solutions.
• Exposure to dbt: Experience with dbt is valuable for applying data transformation techniques in data engineering solutions.