Big Data Engineer II

Key job responsibilities

• Evolve the Revenue technology stack to support AWS's rapid expansion while maintaining compliance with security policies, architectural standards, and operational best practices
• Design and build end-to-end data pipelines that transform raw data from diverse upstream sources into actionable business insights powering quota management, forecasting, and compensation decisions
• Develop frameworks, tools, and AI-driven solutions that eliminate manual processes, reduce operational overhead, and accelerate time-to-insight for Revenue customers
• Create and maintain dimensional data models and data structures that enable self-service analytics and support evolving reporting requirements across Finance, Sales Operations, and Analytics teams
• Mentor a team of Data Engineers to deliver cross-functional solutions, foster technical growth, and establish engineering excellence standards
• Architect and optimize Revenue data infrastructure. Ensure enterprise-grade security, cost efficiency, and scalability while processing billions of daily transactions across 20+ data sources
• Collaborate with product managers, stakeholders, and customers to translate business requirements into technical solutions

About the team

About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Basic Qualifications

• 3+ years of data engineering experience
• 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
• 3+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• Bachelor's degree or above in Computer Science, Computer Engineering, Data Science, Electrical Engineering, or majors relating to these fields, or 3+ years of professional software development experience
• Experience in at least one object-oriented programming language (e.g., JavaScript, Python, C#)

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR