Job Overview
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.
Key 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.
- Conduct rapid prototyping, proof-of-concepts, and automation tooling to benchmark, validate, and improve data collection, processing, and analytics.
- Collaborate across teams to ingest, transform, and integrate data from diverse sources using AWS big data technologies.
- Champion best practices in data integrity, testing, validation, monitoring, and documentation in a fast-paced environment.
- Proactively identify opportunities to improve system reliability, scalability, and efficiency while solving problems at their root.
A Day in the Life
A typical day for a Data Engineer II on the Investments Platform at AWS blends deep technical work, collaboration, and innovation at massive scale in a highly agile environment.
You kick off with a quick stand-up to align on shifting priorities—requirements evolve rapidly, much like a startup, which is exactly how AWS operates to stay ahead in a fast-moving landscape.
Mornings focus on monitoring overnight pipeline runs (Glue, EMR, Lambda), debugging Redshift/S3 flows, or optimizing queries for cost and performance.
Midday involves building pipelines, designing schemas, or prototyping GenAI features with Bedrock/Nova/ Q to automate insights and workflows.
Afternoons include cross-team syncs with product and program leaders to refine requirements and deliver dashboards that drive decisions.
You close by documenting progress, testing changes, or exploring new tools—embracing constant adaptation, ownership, and high-velocity delivery.
About the Team
The Investments Platform team at AWS is a high-velocity, highly agile group operating with startup-like speed and ownership in a massive enterprise environment.
We thrive on rapidly evolving requirements, frequent pivots, and bold experimentation—hallmarks of how AWS stays ahead in a fast-moving world.
Our small, cross-functional team includes data engineers, product managers, program leaders, and GenAI specialists who collaborate closely to deliver secure, scalable data solutions that power strategic decisions for Amazon's key customers.
We value initiative, quick iteration, and end-to-end impact over rigid processes, fostering an environment where you own outcomes from idea to production at global scale.
Basic Qualifications
- 5+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes.
- 5+ years of developing and operating large-scale data structures for business intelligence analytics using SQL.
- 5+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle.
- Experience with data modeling, warehousing and building ETL pipelines.
Preferred Qualifications
- 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).
- Experience with generative AI tools such as Amazon Bedrock, Nova, Amazon Q, Kiro.
- Strong understanding of the broader GenAI ecosystem and its application to real-world data engineering challenges.
EEO Statement
Amazon is an equal‐opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Benefits and Compensation
The base salary range for this position is 132,100.00 – 178,800.00 USD annually, located in Seattle, WA, USA. Your Amazon package will include sign‐on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.
Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and optional Supplemental life plans), Employee Assistance Program, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage, 401(k) matching, paid time off, and parental leave.
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