Senior Business Intelligence Engineer, Defects Reduction
DESCRIPTION
Have you ever ordered a product on Amazon and wondered about the complex processes and systems running behind the scenes to power our operations? If so, this role is for you!
• Operations is at the heart of the Amazon customer experience. Each action we undertake is on behalf of our customers, and surpassing customer expectations is our passion.
• We improve customer experience by continuously optimizing the complex movements of goods from vendors and sellers to customers throughout Europe.
• This role requires an individual with analytical abilities, as well as outstanding business acumen and comfort with technical teams and systems.
• The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment.
Our operations teams are transversal centers of expertise, composed of engineers, analysts, scientists, technical program managers, and developers. We focus on defects reduction among the complex problems, operational processes, key tradeoffs, and critical decisions at Amazon.
• We work with fulfillment centers, transportation, finance, and retail teams across the world, to assess impactful defects, define and implement short and long-term improvement plans.
• Defects Reduction connects with core operational organizations responsible for our fulfillment centers, internal and external transportation capabilities, customer returns, and finance teams.
• We obsess about our end-to-end supply chain to make it efficient, drive out defects for our customers, and continuously reduce waste from processes. Our overall mission is simple: we strive towards reaching zero defects across our end-to-end operations.
Key job responsibilities
This role requires an individual with analytical abilities, as well as business acumen and comfort with technical teams and systems. You will lead data analysis and insight generation efforts to support the Defects Reduction program across Europe and North America. This role requires navigating highly complex, strategic scope across the end-to-end supply chain, understanding core operational activities, exposing defects and inefficiencies, surfacing tradeoffs between cost, customer experience, growth, and long-term profitability. The role includes 80% analytical activities and 20% stakeholder/project management.
Data Analytics:
Autonomously develop and lead design, validation, and execution of advanced metrics, reporting and bridging capabilities to support the Defects Reduction program across Operations from inbound, fulfillment, transportation, to customer returns.
You will transform data into insights and improve complex processes across the entire supply chain, working with partner operations and data science teams to identify and eliminate defects.
Perform detailed data set investigations, quality checks, proactively identifying and fixing discrepancies, and establishing modular connectivity between data sets across the wide variety of operational data sources.
Perform deep-dives and data analysis using SQL (>10TB) to uncover insights for known and new defects.
Provide recommendations for initiatives and establish metrics to drive business actions and trade-off decisions.
Stakeholder/Project management:
Develop and share insights with partner teams across supply chain, to influence the immediate defect reduction priorities, and build a 3-year roadmap of initiatives to reach zero defects across our end-to-end operations.
For complex and ambitious opportunities, design and launch pilots, build business cases, expose tradeoffs, show bottlenecks, highlight risks required to solve in order to maximize defect reduction impact.
For algorithmic opportunities, work with partner data science teams, software developers, and research scientists, to design and guide the next round of innovative solutions to drive large step change improvements.
Lead regular reviews with partner teams to monitor the progress of projects across the roadmap.
Consolidate progress into crisp and concise data-driven status updates. You will own reporting to Amazon senior leadership (SVP/VP-level).
A day in the life
Snr. Business Intelligence Engineer starts the day by analyzing various defect data sets (damages, concessions, lost items, efficiency losses under the roof and on the road, collaborating with cross-functional teams to assess processes and generate insights. They create reports and dashboards to help decision-making for operations stakeholders. They work closely with operational data science teams, tech software developers, applying BI tools to maximize defect reduction initiatives. Solving complex problems related to defects, they contribute to Amazon's goal of providing exceptional customer experiences and lowering the cost-to-serve for customers.
About the team
Defects Reduction team works across operations, from inbound, fulfillment, transportation, to customer returns, and finance. We help drive defects reduction initiatives, balancing between customer experience, cost and operational process efficiency. The team has a large scope of impact and regularly interacts with leadership multiple levels above.
BASIC QUALIFICATIONS
- Experience working directly with business stakeholders to translate between data and business needs
- Experience with SQL
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience in the data/BI space
PREFERRED QUALIFICATIONS
- Experience managing, analyzing and communicating results to senior leadership
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.