Senior Data Engineer, AWS Specialist and Partner Organization

Description AWS is one of Amazon’s largest and fastest growing businesses, serving millions of customers in more than 190 countries. We use cloud computing to reshape the way global enterprises use information technology. We are looking for entrepreneurial, analytical, creative, flexible leaders to help us redefine the information technology industry. If you want to join a fast-paced, innovative team that is making history, this is the place for you.

The ASP Data Engineering Team supports the data needs of the AWS Specialist and Partner Organization, a worldwide team of specialists and partners helping customers transform their businesses through AWS’s Core, GenAI, and Partner services and solutions.

Key job responsibilities

The successful candidate will be an expert with SQL, ETL (and general data wrangling), with experience leveraging cloud-based data services such as AWS EMR, Glue, Firehose, Lambda, and similar technologies, and have exemplary communication skills. The candidate should have hands-on experience with AI/ML technologies, including large language models (LLMs), and a strong understanding of designing and building Agentic Frameworks — including autonomous agents, multi-agent orchestration, tool integration, and retrieval-augmented generation (RAG) pipelines. The candidate will need to be comfortable with ambiguity in a fast-paced and ever-changing environment, and able to think big while paying careful attention to detail. The candidate will be passionate about working with huge data sets, leveraging AI-driven approaches to unlock insights, and someone who loves to bring data together to answer business questions and drive growth.

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

• 5+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience in writing complex, highly-optimized SQL queries across large datasets

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience operating large data w…