Engage with business stakeholders to translate business requirements into technical data engineering tasks and project deliverables Design and implement data pipelines using Azure Data Factory, Databricks, and Azure Synapse to process, transform, and load data from various sources into the Azure ecosystem Create data models to support data integration, analytics, and reporting needs Develop and manage ETL pipelines using Azure Data Factory and SQL to extract, transform, and load data into data lakes and data warehouses Automate data processing workflows using Databricks, Azure Functions, or Logic Apps for real-time and batch data integration Monitor and optimize pipeline performance to ensure efficiency and minimize downtime Implement and manage cloud data solutions, ensuring high availability, disaster recovery, and compliance within the Azure environment Integrate data from multiple sources such as on-premises databases, cloud-based applications, APIs, and third-party data sources into Azure services Develop data transformation workflows using Azure Data Bricks, Apache Spark, and SQL for advanced analytics and reporting Ensure compliance with data privacy laws (e.g., GDPR, CCPA Implement CI/CD pipelines using Azure DevOps or GitHub Actions to automate the deployment and testing of data engineering solutions Continuously monitor and refine workflows for automated data processing and integration using triggers, version control, and automated testing Create detailed technical documentation for data architectures, pipelines, processes, and operational workflows Lead the development team to deliver on time as well help team to get unblocked from any issues/challenges Perform PR review & validate for accuracy before check in Skills: PostgreSQL, MySQL, SQL Server, Azure data factory, Azure Synapse, Logic apps, Fabric, ADLS(Azure Data Lake Storage), Azure Databricks, Azure Cosmos DB #J-18808-Ljbffr
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