Data Engineer II, AWS Field Experience - Investments

Amazon • 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.

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our
culture of inclusion. We have ten employee-led affinity groups, reaching 40,000
employees in over 190 chapters globally. We have innovative benefit offerings,
and host annual and ongoing learning experiences, including our Conversations on
Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s
culture of inclusion is reinforced within our 14 Leadership Principles, which
remind team members to seek diverse perspectives, learn and be curious, and earn
trust.

Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours
you spend at home or at work; it’s about the flow you establish that brings
energy to both parts of your life. We believe striking the right balance between
your personal and professional life is critical to life-long happiness and
fulfillment. We offer flexibility in working hours and encourage you to find
your own balance between your work and personal lives.

Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of
experience levels and tenures, and we’re building an environment that celebrates
knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring
and thorough, but kind, code reviews. We care about your career growth and
strive to assign projects based on what will help each team member develop into
a better-rounded engineer and enable them to take on more complex tasks in the
future.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal
opportunity employer and does not discriminate on the bias of race, national
origin, gender, gender identity, sexual orientation, protected veteran status,
disability, age, or other legally protected status. For individuals with
disabilities who would like to request an accommodation, please visit:
https://www.amazon.jobs/en/disability/us.

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

Nice To Haves

• 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 working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
• Knowledge of software engineering practices and best practices for the full software development life cycle, including agile software development, use of software IDEs, use of source control
• Experience working with data and leveraging analytics to make decisions
• Experience in complex problem solving, and working in a tight schedule environment
• Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy

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

• 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

What This Job Offers

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