Sr. Analyst, Global Operational Excellence

September 7, 2026

Office

Senior

Warsaw, Poland

Important before applying

This job has conditions that may affect your decision to apply

Country restriction appliesOffice-only workBusiness travel requiredEnglish is required

Description

Senior Analyst role in Amazon's EU Inbound Supply Chain, focusing on designing scalable data architectures, building analytics systems, and driving strategic decisions through data. Involves real-time streaming and batch processing, with exposure to GenAI tools and cross-functional collaboration.

Responsibilities

Design and own end-to-end data architectures spanning real-time streaming and batch processing, selecting the right paradigm for latency, volume, and criticality.
Build production-grade, scalable ETL/ELT pipelines processing multi-TB datasets daily across Redshift, Athena, S3, and DynamoDB with data-quality checks, monitoring, and alerting.
Architect real-time analytics for operational monitoring: live visibility into inbound flows, delivery accuracy, dock congestion, and network disruptions.
Own metric frameworks and reporting: design KPIs, build automated dashboards, support WBR/MBR narratives, and own the 'why' through root-cause analysis.
Develop GenAI-driven tooling and agentic workflows that automate reporting narratives and root-cause analysis, reducing time-to-insight from days to minutes.
Drive deep-dive investigations across complex, multi-source datasets tracing issues to specific products, warehouses, or routes, then quantifying network-wide impact.

Requirements

Bachelor's degree in a quantitative field such as statistics, mathematics, data science, computer science, economics, engineering, or operations research.
Experience in analytics, data engineering, or business intelligence at a large-scale enterprise, including data-warehouse architecture, data modeling, and ETL/ELT pipeline design.
Advanced SQL and programming (Python or equivalent) to extract, transform, and clean large multi-TB datasets, plus scripting for pipeline automation and scheduling.
Experience with both real-time streaming (e.g., Kinesis, Kafka, Flink) and batch processing (e.g., EMR, Hive) systems, and with data-visualization tools (QuickSight, Tableau, or similar).
Experience translating operational problems into analytical solutions and communicating results to senior leadership with clear business-impact quantification.

Conditions

Company supplementary benefits apply subject to further terms, including pension plans, health insurance, life and disability insurance, business travel insurance, MultiSport card, employee discount code and program, and the Employee Assistance Program.
Exposure to the full data-product lifecycle — from defining metrics to designing architectures, building pipelines, and delivering insights to senior leadership.
Federated stakeholder model working across Engineering, Science, Transportation, Planning, Finance, and Operations.

AWSPythonSQLRedshiftKinesislogistics

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