Amazon Web Services, Inc.
Operations, IT, Support Engineering, Data Engineering, Cloud Computing
DataEngineerII,AWSFieldExperience-Investments
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Engineer II, AWS Field Experience - Investments at Amazon Web Services, Inc.. Skills: Data engineering, AWS, ETL, Data modeling. Design data pipelines. Implement data pipelines”
Industry & Context.
Problem solving; Root cause analysis
What They're Looking For.
Must Have
5+ years data structures experience, 5+ years ETL/ELT experience, 5+ years SQL experience, 5+ years Oracle experience, Data modeling experience, Data warehousing experience, Building ETL pipelines experience
Nice to Have
AWS technologies experience, Non-relational databases experience
What You'll Do.
Design data pipelines
Implement data pipelines
Implement ETL processes
Build storage solutions
Maintain storage solutions
Develop analytics workflows
Automate analytics workflows
Leverage GenAI services
Prototype intelligent features
Automate data workflows
Accelerate insight delivery
Apply GenAI ecosystem
Conduct rapid prototyping
Conduct proof-of-concepts
Develop automation tooling
Benchmark data collection
Validate data collection
Improve data collection
Benchmark data processing
Validate data processing
Improve data processing
Collaborate to ingest data
Collaborate to transform data
Collaborate to integrate data
Champion data integrity best practices
Champion testing best practices
Champion validation best practices
Champion monitoring best practices
Champion documentation best practices
Identify opportunities to improve reliability
Identify opportunities to improve scalability
Identify opportunities to improve efficiency
Solve problems at root
How You'll Work.
Team & Collaboration
Collaborate with product managers; Collaborate with program leaders; Collaborate with data scientists; Collaborate with technical partners; Cross-team collaboration
Full Job Description
Amazon Web Services is seeking a talented and innovative **Data Engineer II** to design, build, and evolve critical data capabilities for our Investments Platform. This platform delivers secure, highly available, scalable, and high-performance data solutions that empower our field teams to deliver exceptional service to Amazon's key customers. Join a dynamic, high-impact team at an exciting stage of product evolution. You'll help shape the future of how AWS manages and derives value from data at massive scale, while collaborating with product managers, program leaders, data scientists, and cross-AWS technical partners. As a Data Engineer II, you'll own end-to-end data solutions — from ingestion and transformation to analytics and insight generation — while incorporating modern generative AI practices to enhance efficiency, automation, and decision-making. Key job responsibilities - Design and implement robust, scalable data pipelines and ETL processes using AWS-native services (e.g., Glue, Lambda, EMR, Kinesis, S3, Redshift/Spectrum). - Build and maintain data models, schemas, and storage solutions across relational (SQL) and NoSQL databases, data lakes, and warehouses. - Develop, automate, and optimize metrics, reports, dashboards, and analytics workflows to drive business insights and data-informed decisions. - Own infrastructure for data processing and analytics (e.g., Redshift clusters, Spectrum, EMR), including performance tuning, cost optimization, and architectural evolution. - Leverage **Amazon Bedrock**, **Nova models**, **Amazon Q**, **Kiro**, and other internal AWS GenAI services to prototype intelligent features, automate data workflows, enhance data quality, and accelerate insight delivery. - Demonstrate strong understanding of the broader GenAI ecosystem and apply it thoughtfully to real-world data engineering challenges in daily projects. - Conduct rapid prototyping, proof-of-concepts, and automation tooling to benchmark, validate, and improve data co
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