Data Engineer-Data Platforms-Azure

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. 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.
• Implement Azure Data Platform: Implement and maintain Azure Data Platform components, including ADLS2, Blob Storage, SQLDW, Synapse Analytics with Spark and SQL, Azure functions with Python, Azure Purview, and Cosmos DB.
• Utilize Open Source Technologies: Apply proficiency in open source technologies like Apache Airflow and dbt, Spark / Python, or Spark / Scala to support data engineering solutions.
• Ensure Seamless Operations: Operate and maintain data engineering solutions to ensure seamless batch and real-time data processing.
• Exposure to Azure Toolset: Proficiency in 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.
• 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.
• Open Source Technologies: Exposure to open source technologies like 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.
• 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. India Data & Analytics Hybrid Professional PUNE, IN PUNE (0063) IBM India Private Limited Analytics Design Pipelines Python Structured Query Language Scala Spark Storage Azure Data Engineering Data pipeline Apache Airflow Azure Cloud Azure Data Factory Data Platform Databricks Open Source Azure Cosmos DB Azure Synapse Analytics Real-time Data Azure Functions