Data Engineer II, AWS Analytics Engineering

Amazon Development Center U.S., Inc.; Seattle (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon Development Center U.S., Inc. is seeking a data engineering lead to own reliability for 200+ data pipelines powering executive dashboards and reports. You will develop and operate ETL/ELT pipelines, utilize Redshift and AWS data services, and drive AI-enabled monitoring and callouts for EC2/Networking analytics.

You will collaborate with Product Managers, Finance, and Sales to deliver scalable, on-demand metrics, while building governance SOPs and self-serve analytics for senior leaders.

Qualifications

• 3+ years of data engineering experience.
• 3+ years building large-scale BI data structures with ETL/ELT processes.
• 3+ years using OLAP technologies and data modeling.
• 3+ years SQL development and Oracle exposure.
• Bachelor’s degree or foreign equivalent in CS, Engineering, IS, Math, or related field.

Responsibilities

• Own reliability and timeliness for 200+ data pipelines powering executive reports.
• Maintain automated alarms for real-time pipeline health.
• Operate weekly/daily business reviews for senior stakeholders.
• Build and maintain dashboards with QuickSight and Weave.

Skills

Data engineering

ETL/ELT

SQL

OLAP

Data modeling

Oracle

Big data architectures

Education

Bachelor’s degree

Tools

Redshift

AWS Glue

EMR

Kinesis

FireHose

Lambda

S3

IAM roles and permissions

Weave

QuickSight

Job description

Own end-to-end analytics for EC2, EBS, and Networking services, powering executive reporting, automated pipeline monitoring, and dashboard experiences.

Responsibilities

• Own reliability and timeliness for 200+ data pipelines powering executive-facing reports.
• Maintain and extend automated alarms for real-time monitoring of pipeline health.
• Use AI-powered agents to self-heal pipeline failures and triage tasks, leveraging Redshift, orchestration frameworks, and AWS data services.
• Operate Weekly/Daily Business Review reporting (WBR/DBR) for EC2 services, ensuring accurate, timely delivery to CEO/S-Team and VP-level stakeholders.
• Operate and improve report generation, validation, and delivery workflows automated via LLMs.
• Generate executive callouts by identifying week-over-week trends, anomalies, and key drivers for 9 services, owning the quality bar for LLM-automated callout generation.
• Continuously improve prompt and pipeline accuracy for callout generation across all assigned services.
• Ingest new data sources and build metrics for business health including usage, capacity, adoption, and customer growth.
• Ensure metrics are sustainable, reproducible, and available on demand using scalable ETL pipelines in Redshift with workflow orchestration.
• Conduct deep-dive analyses for Product Managers, Sales, and Finance teams.
• Author and maintain governed SOPs and analyses within a proprietary analytics platform that supports stored context and pre-built queries.
• Design, build, and maintain interactive dashboards using QuickSight and Weave, covering product trends, customer growth, instance utilization, and feature adoption.
• Improve self-serve dashboard capabilities for service areas.
• Translate business questions into data products with Product Managers and service finance teams; present findings to senior leaders and serve as the primary analytics point of contact for assigned service areas.

Requirements

• 3+ years of data engineering experience.
• 3+ years developing and operating large-scale business intelligence data structures using ETL/ELT processes.
• 3+ years developing and operating large-scale business intelligence data structures using OLAP technologies.
• 3+ years developing and operating large-scale business intelligence data structures using data modeling.
• 3+ years developing and operating large-scale business intelligence data structures using SQL.
• 3+ years developing and operating large-scale business intelligence data structures using Oracle.
• 3+ years in the job offered or a related occupation.
• 1+ years developing and operating large-scale business intelligence data structures using ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform).
• Bachelor’s degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field.
• Experience with data modeling, warehousing, and building ETL pipelines.

Technologies

• Redshift
• Orchestration frameworks
• AWS data services
• ETL, ELT
• OLAP
• SQL
• Oracle
• QuickSight
• Weave
• AWS Glue
• EMR
• Kinesis
• FireHose
• Lambda
• IAM roles and permissions
• S3

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
• 401(k) matching
• Paid time off
• Parental leave
• Sign-on payments and restricted stock units (RSUs)

Preferred Qualifications

• Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
• Experience with non-relational databases/data stores including object storage, document or key-value stores, graph databases, and column-family databases.

About the Team

• EC2 + Networking Product BI team within AWS Analytics & Engineering (AAE).
• Data and analytics partner for Amazon Elastic Compute Cloud (EC2), Networking Services, and adjacent Compute product families, supporting 100+ Product Managers across 11 engagement areas.
• ETL Pipeline Monitoring & Operations: build and operate 200+ pipelines ingesting, transforming, and serving petabyte-scale datasets across EC2, Networking, and Compute services; automated alarms for real-time monitoring and AI-powered agents to self-heal failures and triage tasks.
• Report Delivery & Callout Generation: deliver WBR/DBR reports across 9 Compute services (EC2 Core, Gen AI, EBS, Bedrock, SageMaker, ECS, EKS, ECR, Lambda); report generation, validation, and callout generation are performed via LLMs.
• Data Ingestion & Metric Creation: design and maintain metrics for business health including usage, capacity, adoption, and customer growth, ensuring they are sustainable, reproducible, and available on demand.
• Analysis & Deep Dives: produce analyses for Product Managers, Sales, and Finance teams using a proprietary analytics platform with governed SOPs, context, and prior work to support deep dives with governed data, technical depth, and the right queries.

Location: Seattle, WA (onsite)

Salary: USD 132,100 - 178,800 per year

Minimum experience: 3 years