Senior Data Engineer, Sales Insights, Analytics, Data Engineering and Science

Join the cloud platform trusted by millions worldwide and own the data infrastructure that powers strategic business decisions across Asia Pacific and Japan (APJ). This is a hands-on, technically demanding role for an experienced data engineer who is passionate about building robust data products that enable teams to measure and grow the business. You will be part of a team that operates at the intersection of data engineering, business intelligence, and regional strategy, partnering with key stakeholders (e.g. Sales, Sales Operations, Finance, etc.), and regional leadership to deliver data products that matter. If you thrive in a fast-paced, high-growth environment where ownership, technical depth, and business judgement are equally valued — and where your pipelines, data models, and analytics platforms will serve field teams across key verticals and business units across APJ — this role is for you.

Key job responsibilities

• Own the design, development, and maintenance of the APJ SIADS' data analytics platform, including data pipelines, data lakes, and analytical and visualisation platforms that power SMGS business insights
• Build and maintain APJ-specific data models and pipelines, ensuring alignment between worldwide definitions and APJ business logic, and validating data quality against WW business standards
• Design and maintain the backend data infrastructure for end-user last-mile analytics tools, implementing ETL processes that ensure data is clean, fresh, and optimised for APJ analytical requirements
• Develop monitoring capabilities for data quality and query performance to keep platforms reliable and responsive
• Collaborate on the design and delivery of metrics, reports, analyses, and dashboards that drive key business decisions across APJ, in partnership with key stakeholders e.g., Sales, Sales Operations, Finance, etc.
• Ensure pipelines and data products meet the requirements of field teams across key verticals and business units
• Maintain compliance with information security policies and data governance standards for all infrastructure and software used by the team

About the team

The Sales Insights, Analytics, Data Engineering & Science (SIADS) organisation builds the data infrastructure and analytics products that power business decisions across AWS' Sales, Marketing, and Global Services (SMGS) organisation. We sit at the intersection of engineering and business strategy, partnering with key stakeholders (e.g., Sales, Sales Operations, Finance, etc.) to ensure the right data reaches the right people at the right time. Operating across time zones with both global and regional depth, we value technical excellence, sound business judgement, and clear communication. Amazon's data-driven culture starts here — and your work will be central to it.

Basic qualifications

• 8+ years of data engineering experience
• Competent in performing data transformation using SQL
• Experienced in managing and maintaining data pipelines
• Proficient in cloud computing with Infrastructure-as-Code (IaC)
• Skilled in designing system solutions at scale
• Familiar with leveraging AI-assisted coding tools

Preferred qualifications

• Strong written and verbal communication skills
• Knowledgeable in Apache Spark for large-scale data workloads
• Proficient in serverless ETL using AWS Glue for data ingestion, transformation, and cataloguing
• Skilled in automating data quality validation to detect anomalies and enforce data integrity