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Data Engineer II, Ring NA Sales and Marketing, RBKS Sales & Marketing Analytics

Amazon.com Inc

  • Hawthorne, CA
  • 7 days ago

    Highlights

    In this role, you will: Design, build, and maintain reliable, scalable ETL/ELT pipelines that deliver data to RBKS sales and marketing teams, owning data-readiness SLAs and CloudWatch-based monitoring and observability. You will work with a complicated data environment, employ the right architecture to handle data, and support various analytics use cases including business reporting, production data pipelines, machine learning, and optimization models.

    Numbers & Facts

    LocationHawthorne, CA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    Description

    Ring is seeking a Data Engineer with strong analytical, communication, and project management skills to join our team. This role will work closely with business intelligence engineers, data scientists, and business stakeholders across various verticals. You will design, evangelize, and implement state-of-the-art solutions that help us provide a great customer experience. You will work with a complicated data environment, employ the right architecture to handle data, and support various analytics use cases including business reporting, production data pipelines, machine learning, and optimization models. This role will be expected to utilize GenAI to build reliable, scalable data pipelines, which produce data optimized for our customers, who will also be utilizing AI Agent pipelines.

    Key job responsibilities

    In this role, you will:

    • Design, build, and maintain reliable, scalable ETL/ELT pipelines that deliver data to RBKS sales and marketing teams, owning data-readiness SLAs and CloudWatch-based monitoring and observability.
    • Apply the right architecture for a complex, multi-channel data environment which supports the sell-through pipeline that serves as the single source of truth for Ring & Blink unit sales across 450+ datasets.
    • Leverage GenAI to accelerate development and produce data optimized for both analysts and downstream AI Agent pipelines.
    • Build direct API integrations for new retailers (Costco, Best Buy, Home Depot) using reusable frameworks that enable rapid onboarding without sacrificing reliability.
    • Contribute to large-scale migrations from the Ring Data Warehouse to native AWS and from Tableau to QuickSight and AI-driven reporting.
    • Identify and resolve data quality issues and performance bottlenecks in core pipelines without disrupting daily operations.
    • Enable diverse analytics use cases - business reporting, demand planning, machine learning, and optimization models - by producing clean, query-ready data.
    • Partner with business intelligence engineers, data scientists, and stakeholders across verticals, evangelizing platform standards and best practices.

    A day in the life

    A typical day blends building, collaborating, and maintaining. You monitor pipeline health and data-readiness SLAs across our GTM platforms, triaging issues before stakeholders are impacted. You partner with BIEs and data scientists to refine sell-through data models, scope new retailer API integrations, and advance migration efforts like Clara and Horizon. You leverage GenAI to accelerate pipeline development and harden the data feeding AtlasKB and our Bedrock agents. You participate in code reviews by authoring changes and reviewing work to uphold quality and platform standards. No two days look the same, but each one moves a strategic platform forward.

    About the team

    The RBKS Sales & Marketing Analytics team is the single source of truth for Ring and Blink go-to-market data, including sell-through, forecast, attainment, and inventory. We are a data engineering organization that owns the entire data lifecycle, from production ETL and Redshift cluster and AWS infrastructure to full-stack applications and CI/CD. We operate an extensive data platform along with AtlasKB, our company-wide AI-ready knowledge base. We also lead the GTM organization"s AI strategy, translating enterprise ambition into scalable, production-grade execution. Our work directly powers planning and executive decision-making across the business.

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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