Remote Amazon Data Analyst Jobs in Washington (NOW HIRING)

• Own the end-to-end measurement framework for Greenlight’s devices business across Shopify and Amazon. Define the KPIs, build the reporting, and ensure the team always has a clear, current view of device sales performance.
• Measure the full funnel from ad impression to device purchase to subscriber conversion. Understand which marketing inputs drive device sales and which device buyers become high-LTV subscribers. This two-step conversion is the core analytical problem in this role.
• Analyze paid performance across Amazon Ads and Shopify-driven channels. Evaluate ROAS, CAC, and payback period at the device level and surface recommendations on where to shift spend.
• Dig into the Shopify storefront and Amazon product page funnels. Identify where conversion is leaking, what product, pricing, or creative variables are driving lift, and bring findings forward before stakeholders ask.
• Build and own dbt models that encode business logic for the devices domain in a scalable, reusable way to power dashboards, reporting, and stakeholder self-serve.
• Build and maintain Tableau dashboards that give marketing and leadership a reliable, current view of device sales, channel performance, and subscriber attach rates.
• Use Claude fluently as a daily productivity layer: accelerating SQL, generating documentation, QA-ing work, and building faster analytical workflows. Help define and share best practices for AI-assisted analytics across the team.
• Partner directly with the devices marketing team to scope analytical problems, pressure-test
• Identify gaps before they become problems: data quality, metric definitions, reporting coverage, and stakeholder understanding. Own the fix, not just the flag.

• 4 to 8 years in a data or analytics role with direct experience in e-commerce or retail marketing analytics. You understand how product sales, marketplace channels, and subscription conversion interact.
• Hands-on experience with Shopify analytics and Amazon Seller Central or Amazon Ads. You know how these platforms structure their data, what the key metrics are, and how to measure performance across both.
• Strong, proven SQL ability. You write clean, efficient queries across complex schemas and can build analytics logic others can maintain. dbt experience, including owning models in production, is a strong plus.
• You write readable, well-structured Python for analytical work: data manipulation, automation, or scripting. Experience with pandas and the ability to move fluidly between SQL and Python depending on what the problem calls for is what we’re looking for.
• Proficient with Claude or similar AI tools for analytical work. You use them to move faster, not as a crutch. You know how to validate outputs rather than ship the first answer.
• You understand how attribution models work in a marketplace context, what makes a good experiment, and how to think about LTV, CAC, and payback period for a hardware product that feeds a subscription business.
• You don’t wait to be asked. You spot the gap, scope the work, and drive it to a conclusion. Your stakeholders shouldn’t have to manage your backlog.
• You can take a fuzzy business question and turn it into a clear analytical plan. You ask the right clarifying questions and bring structure without needing the problem handed to you pre-scoped.
• You communicate findings in a way that drives decisions. You know when a chart is enough and when you need a narrative. You’ve presented to senior stakeholders and know how to calibrate.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.