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Key Responsibilities
Design, develop, and maintain scalable data pipelines using Python and PySpark
Build and optimize batch and near‑real‑time data processing workflows
Work on GCP‑based data platforms, integrating multiple structured and semi‑structured data sources
Develop data transformations, validations, and enrichment logic aligned to business requirements
Optimize Spark jobs for performance, scalability, and cost efficiency
Collaborate with data architects, platform teams, and downstream consumers
Implement logging, monitoring, and error‑handling within data pipelines
Ensure adherence to enterprise data governance, security, and compliance standards
Support production deployments and provide L2/L3 support as needed
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