Data Engineer I, Data Engineering

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 fast-paced environment

Key job responsibilities

1. Design/implement automation and manage our massive data infrastructure to scale for the analytics needs of case management.

1. Build solutions to achieve BAA(Best At Amazon) standards for system efficiency, IMR efficiency, data availability, consistency & compliance.

2. Enable efficient data exploration, experimentation of large datasets on our data platform and implement data access control mechanisms for stand-alone datasets

3. Design and implement scalable and cost effective data infrastructure to enable Non-IN(Emerging Marketplaces and WW) use cases on our data platform

4. 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

5. Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.

6. Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations

7. Enjoy working closely with your peers in a group of very smart and talented engineers.

• 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)

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

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