Hiring: AWS Databricks Data Engineer We are looking for an experienced AWS Databricks Data Engineer with strong expertise in Databricks, Azure Data Factory (ADF), PySpark, Python, Terraform, and AWS Cloud . If you have experience building scalable cloud-based data pipelines and are looking for your next prospect, we’d love to connect Job Details Role: AWS Databricks Data Engineer Experience: 6–9 Years Locations: Indore / Pune / Hyderabad Notice Period: Immediate Joiners / 30 / 60 / 90 Days Key Skills: AWS, Databricks, ADF, PySpark, Python, Terraform Key Responsibilities Design, develop, and maintain scalable data engineering solutions using Databricks . Develop high-performance data processing pipelines using PySpark and Python . Build and manage ETL/ELT workflows using Azure Data Factory (ADF) . Work with AWS cloud services for data storage, processing, integration, and deployment. Design and implement efficient data ingestion and transformation frameworks. Develop and maintain cloud infrastructure using Terraform / Infrastructure as Code (IaC) . Optimize Databricks jobs,



Spark workloads, and data pipelines for performance and scalability. Implement data quality, monitoring, logging, and error-handling mechanisms. Troubleshoot production issues related to data pipelines and distributed processing. Collaborate with architects, analysts, DevOps teams, and business stakeholders to deliver reliable data solutions. Follow CI/CD, version control, security, and cloud engineering best practices. Required Skills 6–9 years of experience in Data Engineering / Cloud Data Engineering . Strong hands-on experience with Databricks . Strong development experience in PySpark and Python . Hands-on experience with Azure Data Factory (ADF) . Good experience working with AWS Cloud . Hands-on knowledge of Terraform and Infrastructure as Code . Strong understanding of ETL/ELT, data pipelines, data transformation, and distributed data processing . Experience working with large datasets

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