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hace 2 meses
We are seeking a highly skilled Azure Data Engineer with extensive experience in Databricks, PySpark, and Spark SQL to join our team at Advancio.
Key Responsibilities- Design and Develop Scalable Data Pipelines: Design, build, and maintain large-scale data solutions on Azure, with a focus on real-time and batch data processing using Databricks.
- ETL Process Development: Develop and optimize ETL processes for handling large data sets.
- Data Requirements and Solutions: Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and implement solutions.
- Data Quality and Performance: Ensure data quality, performance, and scalability by implementing best practices for coding and data architecture.
- Data Modeling and Management: Create and manage data models, databases, and data lakes on Azure.
- Pipeline Monitoring and Troubleshooting: Monitor and troubleshoot data pipelines, ensuring high availability and reliability.
- Security and Compliance: Implement security and compliance best practices in the data pipeline, following Azure standards.
- Azure Services Integration: Work with Azure services like Azure Data Factory, Azure Synapse, and Azure Blob Storage to orchestrate and manage data workflows.
- Education: Bachelor's degree in Computer Science, Information Technology, or a related field.
- Experience: 5+ years of hands-on experience with Azure Databricks.
- Skills: Proficiency in PySpark and Spark SQL for building scalable data pipelines. Solid understanding of Azure data ecosystem, including Azure Data Lake, Azure Data Factory, and Azure Synapse Analytics.
- Additional Qualifications: Experience with ETL processes, data modeling, and data architecture. Familiarity with cloud security best practices and data governance. Strong problem-solving and troubleshooting skills. Excellent communication and collaboration skills.
- CI/CD Pipeline Experience: Experience with CI/CD pipelines using tools like Azure DevOps.
- Data Warehousing and Big Data Technologies: Knowledge of Data Warehousing and Big Data technologies.
- Programming Languages: Experience with other programming languages like Python or Scala.
- Machine Learning Workflows: Familiarity with Machine Learning workflows on Databricks.
