Engineering Manager - Data and Analytics, Network Flow and Technologies

- Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
- Experience with R, Python, Weka, SAS, Matlab or other statistical/machine learning software
- Experience working directly with business stakeholders to translate between data and business needs
- Experience leading and influencing the BI strategy of your team or organization
- Experience working with very large data warehousing environment
- Experience managing a data or BI team
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing and certification
- Experience managing, analyzing and communicating results to senior leadership

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Are you a hands-on leader passionate about automation, logistics and solving complex problems at vast scale? Join our mission to build foundational systems that shape the future of Amazon's global fulfillment network.

As a Business Intelligence Manager, you will be responsible for leading a team of motivated engineers in design, development, test and launch of new features and products. You will own services which model Amazon's fulfilment network capabilities and constraints, enabling optimization for how Amazon fulfils an item from click until delivery. These services improve customer experience by providing faster promises and drive fulfillment planning and execution to lower transportation cost.

Key job responsibilities
- Lead and manage a team of junior and mid-level business intelligence engineers, data engineers and software development engineers
- Establish team business practices, roles and responsibilities, and professional development opportunities
- Build and maintain the data infrastructure to answer business questions with data using data engineering best practices
- Define the data engineering processes that leverage various AWS services to improve accessibility, redundancy, data integrity, cost, and storage requirements.
- Collaborate with Data Engineers, Business Intelligence Engineers, Data Scientists, Business Analysts, and Product/Program Managers to understand the business and technical requirements, and make decisions that help make the products/programs smoother.
- Interface with other technology/data engineering teams to extract, transform, and load data from a wide variety of data sources using and AWS data technologies.
- Lead the technical design and implementation of the data infrastructure.
- Design and manage data audit, quality, and reconciliation processes in collaboration with various stakeholders.

A day in the life
To be successful in the role, you need strong team management, communication and analytical skills, alongside with the ability to manage stakeholders’ expectations to deliver the strategic plan with your team. You will work in a collaborative and empowering work environment where cross-functional teamwork drives success, and your expertise in data-driven innovation is highly valued. You’ll have the autonomy to lead initiatives, the support to grow professionally, and the opportunity to make a meaningful impact by delivering actionable insights that shape key business decisions.

If you need us to make any adjustments throughout the recruitment process due to a disability (including, but not limited to neurodiverse or mental health conditions), or any other health issue please let us know by contacting emea-ops-enable@amazon.com.

About the team
The Network Flow and Technologies (NFT) team is responsible for building data solutions that drive operational efficiency and enhance the Amazon customer experience. We work across the supply chain to optimize for the network, while minimizing complexity and reducing variation to ensure streamlined operations and consistent outcomes. By providing comprehensive reporting, insightful attribution, and accurate forecasting, we empower our stakeholders to understand what happened, why it happened, and what will happen next. We own the results, not just the technology. We rigorously audit outputs with metrics and experiments, ensuring accuracy and holding dependencies accountable for input quality.