Solutions Architect III, Internal Audit Data Analytics

Amazons Internal Audit organization covers all of AWS Stores & Delivery Operations and Subsidiaries. The Data Analytics team is responsible for the analytical tooling that makes that coverage possible and right now that tooling is spread across several sub-teams each operating their own dashboards risk models and data pipelines. These tools work well independently but they havent been integrated into a single testing pipeline which means audit teams still manually piece together outputs from different systems before they can run a test.

You will own the integration strategy that brings these pieces together. The work starts with understanding what each team has already built and why they built it that way. Dashboards dont feed into risk models. Data pipelines dont inform test generation. Science outputs sit in notebooks instead of running in production. Youll evaluate which AWS services and internal builds fit each integration point write the technical design for how they connect and then work across teams to implement it. You dont hand off implementation you make the technical calls and you write the code.

That also means navigating disagreement. Several teams built their tools for different purposes under different architectural constraints and they wont always agree on data models pipeline patterns or what to prioritize. Before you propose changes you need to understand the real constraints behind each teams decisions. Your credibility comes from what you build not your title.

Most Solutions Architect roles at Amazon are customer-facing and advisory. This one is internal-facing and hands-on. Your customers are Internal Audits audit teams the people who carry testing to the business and assure risk coverage across the enterprise. You sit within the Data Analytics team report to the Head of Internal Audit Data Analytics and work as an integration partner across the sub-teams rather than belonging to any one of them. The goal isnt just a faster pipeline. Its a platform audit teams can actually use without building workarounds for every engagement.

The team is also investing in agentic technology to move Internal Audit from reactive to proactive testing. The target state is agentic pipelines that surface risk and generate test procedures before teams even open an engagement. Applying LLM-driven orchestration to audit testing at this scale hasnt been done before on this team so youll be defining the patterns rather than following an existing playbook and building expertise that few organizations have yet.

This is a highly visible technical individual contributor role that spans Internal Audits full domain. If youre comfortable operating where the mission is clear but the technical path isnt wed like to hear from you.

Key job responsibilities
- Own the integration architecture across BI/Analytics Applied Science and Data Engineering sub-teams designing the pipeline that connects analytical tooling risk models and data infrastructure into a unified testing workflow.
- Write SQL build ETL/ELT processes create data models and implement agentic workflows using LLM orchestration and tool-use chains with human-in-the-loop validation to move audit testing from reactive to proactive.
- Investigate architectural constraints and competing priorities across sub-teams drive alignment on data models and pipeline patterns and resolve technical disagreements through hands-on analysis rather than positional authority.
- Author 6-pagers technical design documents and reference architectures; present architecture decisions and trade-offs to Director and VP-level audiences within Internal Audit leadership.
- Define reusable patterns for agentic audit pipelines that surface risk generate test procedures and speed up engagement execution across the enterprise.

A day in the life
You might start by reviewing a data pipeline prototype with the Data Engineering sub-team working through schema decisions that affect downstream risk models. By midday you could be presenting an integration architecture proposal to Internal Audit leadership walking through trade-offs and fielding technical the afternoon you may pair with the Applied Science team to wire an LLM-driven orchestration step into the testing workflow then close the day drafting a technical design document that captures decisions made and open items for the next sprint.

About the team
The Data Analytics team sits within Amazons Internal Audit organization and provides the analytical tooling that supports audit coverage across AWS Stores and Delivery Operations and Subsidiaries. Three sub-teams (BI/Analytics Applied Science and Data Engineering) each bring specialized capabilities and this role exists to integrate them into a single testing pipeline. We report to the Head of Internal Audit Data Analytics and are investing in agentic technology to make audit testing proactive rather than reactive. If you want to define new patterns at the intersection of data engineering applied science and LLM-driven automation this is the team to do it.

- 8 years of specific technology domain areas (e.g. software development cloud computing systems engineering infrastructure security networking data & analytics) experience
- 5 years of design implementation or consulting in applications and infrastructures experience
- 10 years of IT development or implementation/consulting in the software or Internet industries experience

- Cloud Technology Certification (such as Solutions Architecture Cloud Security Professional or Cloud DevOps Engineering)
- Experience within specific technology domain areas (e.g. software development cloud computing systems engineering infrastructure security networking data & analytics).
- Experience working with end user or developer communities
- Experience managing relationships with SAP customers and partners
- Experience in SAP clean core design concepts including design and build using non-SAP technologies in domains such as Generative / Agentic AI and data & analytics

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

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The base salary range for this position is listed below. 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 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 WA Seattle - 153600.00 - 207800.00 USD annually