Data Engineer I, AWS WW Field Enablement, Analytics and Product Operations

DESCRIPTION

AWS Worldwide Field Enablement (WWFE) is looking for a Data Engineer helping us evolving our data infrastructure to next phase of providing insights through AI based solutions. You'll create data solutions that will optimize existing workflows providing better insights. You will have access to entire AWS AI stack to create next generation data solutions for AI based productivity tools and automation.

AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow.

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.

Key job responsibilities

• Design, build, and optimize logical data models and data pipelines for complex datasets

• Own ongoing data quality and create self-service access to datasets for business intelligence, AI based tools and Model Context Protocols (MCP)

• Improve metadata for better AI results

• Collaborate with Program Managers, Technical Program Managers and other Data Engineers to design stable, performant data solutions

• Write secure, stable, testable, and maintainable code with minimal defects

• Apply appropriate data design approaches and make judicious trade-offs without over-engineering

• Optimize resource usage including system hardware, data storage, query optimization, and AWS infrastructure

• Participate actively in code reviews, design discussions, and team planning

• Resolve root causes of complex problems and balance customer requirements with team needs

• Stay current on distributed systems technologies (MapReduce, MPP architectures, NoSQL databases)

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

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

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.

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

BASIC QUALIFICATIONS

• 2+ years of data engineering experience

• Experience with data modeling, warehousing and building ETL pipelines

• Bachelor's degree or above in a quantitative/technical field such as computer science, engineering, statistics

• Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model

• Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

PREFERRED QUALIFICATIONS

• Experience with big data technologies such as: Hadoop, Hiv