Data Engineer II, Amazon Now
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Monthly Salary:
Posted on:
16 days ago
Vacancies:
1 Vacancy
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Job Summary
We are SCOPE(Supply Chain Operations Planning and Efficiency) team a part of Amazon Now(Tez). We are innovative quick-commerce offering that delivers everyday essential products to customers in just 10 minutes. We build systems to peer into the future and estimate the most cost-effective way to distribute tens of millions of products every week to Amazon team utilizes the latest applications in science machine learning and scalable distributed software on the Cloud to automate and optimize inventory and shipments under the ever-changing landscape of demand pricing and are data-driven dive deep and make decisions based on data while proactively managing risks and seeing the bigger team strives for simplistic and intuitive solutions that reduce complexity add transparency and improve visibility.
Were seeking a Data Engineer II who will own the near real-time data infrastructure powering our AI/ML based forecasting platform for SCOPE. This role focuses on building high-performance streaming pipelines optimizing embedding freshness and implementing global latency strategies to ensure we deliver up-to-date low-latency insights across QC network. You will play critical role in scaling AI-driven analytics across multiple regions while balancing performance and cost.
Key job responsibilities
- Design and implement streaming data pipelines to process high-volume near real-time data from multiple sources.
- Build and maintain the infrastructure supporting large language models including embedding generation vector storage and retrieval systems.
- Develop and optimize a modern data lakehouse to support both batch and real-time analytics workloads.
- Implement caching strategies query optimization and multi-region deployment to achieve sub-second response times.
- Balance performance requirements with cost considerations through efficient resource utilization and workload optimization.
- Ensure data reliability freshness and compliance across the entire data pipeline.
- 3 years of data engineering experience
- 4 years of SQL experience
- Experience with data modeling warehousing and building ETL pipelines
- Experience with AWS services including S3 Redshift Sagemaker EMR Kinesis Lambda and EC2
- 5 years of SQL experience
- Experience with AWS technologies like Redshift S3 AWS Glue EMR Kinesis FireHose Lambda and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage document or key-value stores graph databases column-family databases)
- Knowledge of cloud computing services or deployment architecture
- Experience building data pipelines or automated ETL processes
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 youre applying in isnt listed please contact your Recruiting Partner.
Were seeking a Data Engineer II who will own the near real-time data infrastructure powering our AI/ML based forecasting platform for SCOPE. This role focuses on building high-performance streaming pipelines optimizing embedding freshness and implementing global latency strategies to ensure we deliver up-to-date low-latency insights across QC network. You will play critical role in scaling AI-driven analytics across multiple regions while balancing performance and cost.
Key job responsibilities
- Design and implement streaming data pipelines to process high-volume near real-time data from multiple sources.
- Build and maintain the infrastructure supporting large language models including embedding generation vector storage and retrieval systems.
- Develop and optimize a modern data lakehouse to support both batch and real-time analytics workloads.
- Implement caching strategies query optimization and multi-region deployment to achieve sub-second response times.
- Balance performance requirements with cost considerations through efficient resource utilization and workload optimization.
- Ensure data reliability freshness and compliance across the entire data pipeline.
- 3 years of data engineering experience
- 4 years of SQL experience
- Experience with data modeling warehousing and building ETL pipelines
- Experience with AWS services including S3 Redshift Sagemaker EMR Kinesis Lambda and EC2
- 5 years of SQL experience
- Experience with AWS technologies like Redshift S3 AWS Glue EMR Kinesis FireHose Lambda and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage document or key-value stores graph databases column-family databases)
- Knowledge of cloud computing services or deployment architecture
- Experience building data pipelines or automated ETL processes
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 youre applying in isnt listed please contact your Recruiting Partner.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
About Company
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