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mbtedge is seeking a highly skilled Senior PySpark Developer to drive a large-scale cloud transformation. You will design, develop, and optimize scalable data pipelines on CDP, Iceberg, Airflow, and AWS to support analytics, reporting, and operations.
The role requires deep expertise in distributed data processing, performance tuning, data quality, and cloud-native architectures, with involvement from requirements through production support.
We are seeking a highly skilled Senior PySpark Developer to support a large-scale cloud transformation initiative focused on building modern data platforms on Cloudera, Apache Iceberg, Airflow, and AWS. The role will be responsible for designing, developing, and optimizing scalable data pipelines that ingest, transform, and process large volumes of enterprise data. The successful candidate will work closely with data architects, business analysts, cloud engineers, and application teams to build reliable, high-performance data solutions supporting analytics, reporting, and operational workloads. Responsibilities include developing PySpark applications, implementing ETL/ELT processes, designing Iceberg-based data models, orchestrating workflows using Airflow, and leveraging AWS services to support cloud-native data processing. This requires strong expertise in distributed data processing, performance tuning, data quality, and cloudbased architectures. The candidate will participate in end-to-end solution delivery, from requirements analysis and solution design through development, testing, deployment, and production support. They will also contribute to establishing best practices, reusable frameworks, CI/CD processes, and data governance standards across the platform. The ideal candidate is a hands-on developer with deep technical expertise in modern data engineering technologies and experience working in large-scale enterprise cloud migration and modernization programs.