Amazon Web Services, Inc.
Technology
DataEngineerII,AWSFieldExperienceInvestments
“Data Engineer II, AWS Field Experience - Investments at Amazon Web Services, Inc.. Skills: Data Engineering, AWS, ETL, GenAI. Design data pipelines. Implement data pipelines”
What You'll Achieve.
Deliver exceptional service; Derive value from data; Enhance efficiency; Enhance automation; Enhance decision-making; Accelerate insight delivery; Drive business insights; Drive data-informed decisions
Industry & Context.
Complex problem solving; Root cause analysis
What They're Looking For.
Must Have
5+ years developing data structures for BI analytics using ETL/ELT, 5+ years developing data structures for BI analytics using SQL, 5+ years developing data structures for BI analytics using Oracle, Experience with data modeling, Experience with data warehousing, Experience building ETL pipelines
Nice to Have
Experience with AWS technologies, Experience with non-relational databases, Experience working with Data & AI technologies, Knowledge of software engineering practices, Experience working with data and leveraging analytics, Experience in complex problem solving, Experience working in a tight schedule environment, Experience communicating with users, Experience communicating with technical teams, Experience communicating with senior leadership
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
Optimize analytics workflows
Own data processing infrastructure
Own analytics infrastructure
Tune Redshift clusters
Optimize Redshift costs
Optimize Spectrum costs
Evolve Redshift architecture
Evolve Spectrum architecture
Evolve EMR architecture
Leverage Amazon Bedrock
Prototype intelligent features
Automate data workflows
Accelerate insight delivery
Apply GenAI ecosystem knowledge
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
Ingest data from diverse sources
Transform data from diverse sources
Integrate data from diverse sources
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 their 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
Communication Scope
Requirements gathering; Describe software features; Describe technical designs; Describe product strategy
Process & Methodology
Agile software development
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