Description PCMIE Data Engineering team builds and operates data infrastructure supporting reporting and analytics for Paragon Case Management system serving 180 tenants across Amazon Our customers include teams across Amazon that perform analysis on cases across Paragon tenants from Frontline Operations Training Quality Analytics Science Engineering and Program teams as well as Root Cause Owners and Finance teams who use data for operational planning and upstream defect analysis The data infrastructure built on Native AWS and CDO technologies provides centralized analytics for real-time business health monitoring retrospective process analysis and AI ML-driven automation initiatives The team operates data pipelines across CDO technologies Datanet Cradle DJS and AWS Big data services Glue Lambda RDS with real-time capabilities supporting workforce management and agent productivity A Data Engineer DE in this team works to implement and maintain scalable data solutions They collaborate with cross-functional teams including product managers science and analytics teams to support data-focused initiatives The DE contributes to engineering excellence by identifying and addressing data pipeline inefficiencies implements CDK-based solutions following established best practices and ensures SLA compliance for data delivery They work on core Paragon capabilities including routing case storage and lifecycle management while supporting platform migrations and tenant experience improvements The role involves hands-on development of batch and real-time data pipelines optimization of existing data processes and collaboration with senior team members on architectural decisions and data platform GenAI initiatives They contribute to the team s operational excellence by maintaining data quality standards and supporting stakeholder requirements in a quick-paced environment Key job responsibilities 1 Design implement automation and manage our massive data infrastructure to scale for the analytics needs of case management 2 Build solutions to achieve BAA Best At Amazon standards for system efficiency IMR efficiency data availability consistency compliance 3 Enable efficient data exploration experimentation of large datasets on our data platform and implement data access control mechanisms for stand-alone datasets 4 Design and implement scalable and cost effective data infrastructure to enable Non-IN Emerging Marketplaces and WW use cases on our data platform 5 Interface with other technology teams to extract transform and load data from a wide variety of data sources using SQL Amazon and AWS big data technologies 6 Must possess strong verbal and written communication skills be self-driven and deliver high quality results in a fast-paced environment 7 Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations 8 Enjoy working closely with your peers in a group of very smart and talented engineers Basic Qualifications - 1 years of data engineering experience - Experience with data modeling warehousing and building ETL pipelines - Experience with one or more query language e g SQL PL SQL DDL MDX HiveQL SparkSQL Scala - Experience with one or more scripting language e g Python KornShell Preferred Qualifications - Experience with AWS technologies like Redshift S3 AWS Glue EMR Kinesis FireHose Lambda and IAM roles and permissions Our inclusive culture empowers Amazonians to deliver the best results for our customers If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information If the country region you re applying in isn t listed please contact your Recruiting Partner

📌 Data Engineer I, Data Engineering - Paragon Case Management (Bengaluru)
🏢 Amazon
📍 Bengaluru