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About the role
Azure Databricks, Azure Synapse Analytics, and other Azure services. - Data engineering tools like Apache Spark, Apache Kafka, and Apache Hadoop. - Cloud computing platforms like Azure - Programming languages like Python - Excellent communication and collaboration skills. - Strong problem-solving and analytical skills. - Ability to work in a fast-paced environment and adapt to changing requirements. Design and Implement: Design and implement scalable, secure, and efficient data pipelines using Azure Databricks, Azure Synapse Analytics, and other relevant Azure services. Data Engineering: Develop and maintain data architectures, data models, and data governance policies to ensure data quality and integrity. Azure Databricks: Lead the development and deployment of Azure Databricks workloads, including data ingestion, data processing, and data visualization. Collaboration: Collaborate with cross-functional teams, including data scientists, data analysts, and business stakeholders to understand business requirements and develop solutions. Security and Compliance: Ensure the security and compliance of data pipelines and architectures, adhering to organizational and regulatory standards. Troubleshooting: Troubleshoot and resolve complex technical issues related to Azure Databricks, data pipelines, and data architectures. Mentorship: Mentor junior engineers and provide technical guidance on Azure Databricks, data engineering, and cloud computing
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