We are looking for an innovative, highly motivated and experienced engineer who can think holistically through multidimensional problems. The ideal candidate will have expertise in system integration, gap identification both tactical and strategic, with continuous improvement mindset. You will work closely with engineering teams, product managers, program managers, business development managers and org leaders to deliver end-to-end data driven solutions aimed at continuously enhancing overall business of Last Mile engineering. In this role, you will dive deep into disparate datasets to improve our understanding of various teams and processes involved in Last Mile delivery, build decision-driven analytics that systematically track the overall quality of the Last mile business and program health, improve tooling to reduce cognitive load for our engineers, and extract actionable insights to drive deliverables. You will work on web development, QuickBase reporting mechanisms and backend systems to optimize Last mile engineering efforts.

The Performance Engineering and Quality Assurance team is focused on measuring and continuously improving the performance of Amazon’s Last Mile delivery station processes and operational layouts across safety, cost, associate experience, and efficiency metrics. You will work closely with stakeholders to translate business requirements into scalable, automated solutions that enable data-driven decision making.

As an Amazon Operations Engineer you will be working in one of the world's largest and most complex data warehouse environments. You should have deep expertise in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. You should be expert at designing, implementing, and operating stable, scalable, low-cost solutions to flow data from production systems into the data warehouse and into end-user-facing applications. You should be able to work with business customers in understanding the business requirements and implementing reporting solutions. The potential candidate will explore and utilize in-house tools for machine learning solutions to innovate and find most efficient solution for complex engineering problems.

Above all you should be passionate about building tools and mechanisms to drive change by bringing large datasets together and answering complex business questions.



Key job responsibilities
- Partner with internal stakeholders across multiple teams, gathering requirements and delivering end to end solutions.
- Partner with data engineers to identify the source of data and create a data pipeline to collect necessary business inputs to deliver the analytical product.
- Support pilot studies by building robust pilot analyses plan, data collection processes, and analyzing the output to deliver final recommendations.
- Utilize predictive analytics, machine learning and generative tools to continuously improve the quality of the engineering projects
- Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.
- Design, develop, and implement dashboards, reports, and analytical tools to support the design and process engineering teams.
- Maintain and enhance existing products.
- Apply advanced analytics techniques, including predictive modeling and machine learning, to uncover meaningful trends and recommend impactful improvements.
- Ensure solutions are scalable, maintainable, and follow best practices in data management and visualization.
- Continuously optimize data pipelines, reporting processes, and analytical workflows to improve operational efficiency.
- Mentor and share knowledge with the broader team of process and design engineers.