Data Engineer II, AWS Field Experience - Investments

Amazon Web Services • Seattle, WA

1d

About The Position

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. 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. 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. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Requirements

• 5+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
• 5+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• 5+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
• Experience with data modeling, warehousing and building ETL pipelines
• 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)

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 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.

Benefits

• Amazon also offers comprehensive benefits including 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, and parental leave.
• Learn more about our benefits at https://amazon.jobs/en/benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed