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Company DescriptionBlend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com.Job DescriptionWe are looking for an experienced Azure Databricks Engineer with strong hands-on expertise in Python, SQL, and Apache Spark to design, build, and optimize scalable data pipelines and analytics solutions on the Azure cloud platform. The ideal candidate should have experience working with large datasets, distributed data processing, and modern data engineering practices. Responsibilities Design, develop, and maintain scalable data pipelines using Azure DatabricksImplement ETL/ELT workflows using PySpark, Spark SQL, and PythonOptimize Spark jobs for performance, cost, and scalabilityWork with structured and semi-structured data (Parquet, Delta, JSON, CSV)Build and manage Delta Lake tables (ACID, time travel, schema evolution)Integrate Databricks with Azure Data Lake Storage (ADLS Gen2)Develop complex queries and transformations using SQLCollaborate with data scientists, analysts, and stakeholders to support analytics and ML use casesEnsure data quality, validation, and monitoringFollow best practices for security, access control, and governance in AzureQualifications6+ years of experience in Data EngineeringStrong hands-on experience with Azure DatabricksProficiency in Python for data processingStrong knowledge of SQL (joins, window functions, performance tuning)Hands-on experience with Apache Spark / PySparkExperience with Delta LakeKnowledge of Azure Data Lake Storage (ADLS Gen2)Understanding of distributed computing conceptsExperience with Git version controlAdditional InformationExperience with Azure Data FactoryExposure to CI/CD pipelines (Azure DevOps, GitHub Actions)Basic understanding of data modelingFamiliarity with cloud security and RBAC in AzureExposure to streaming data (Spark Structured Streaming, Event Hub, Kafka)
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