Data Engineer, Associate Experience, Amazon Customer Service

Amazon Customer Service (CS) handles hundreds of millions of customer interactions every year. The Associate Experience team builds the technology that customer service associates use to resolve them: the contact handling workspace AI-assisted resolution tools and the systems that measure service quality. As a Data Engineer on this team you will build the data foundation that measures how these products are helping us deliver customer service at scale and how we can further improve them.

The future of customer service depends on how effectively associates and AI systems work together with associates applying the judgment empathy and context that customers need most. Making that partnership work starts with answering three questions with confidence: Are we delivering service were proud of Did we resolve the customers problem Are associates set up to do their best work Answering them at scale requires the datasets pipelines and data contracts you will design and own.

Your datasets become the source of truth for how Amazon Customer Service measures and improves itself.

Key job responsibilities
- Design and build scalable ETL/ELT pipelines that ingest billions of daily interaction events from diverse sources using AWS technologies such as Redshift Glue EMR Kinesis Lambda and S3
- Design data models and schemas that make high-volume event data documented queryable and performant for analytics science and AI use cases
- Define and enforce data contracts quality checks and freshness SLAs adopted by engineering and science teams across the organization
- Build ML-ready datasets and feedback loops that power automated quality measurement AI model training and continuous improvement of associate tools
- Own monitoring alerting and observability for your pipelines proactively identifying and resolving data quality issues before consumers are impacted
- Modernize existing data infrastructure proposing architectural improvements that increase reliability reduce cost and improve performance
- Break down ambiguous business questions into concrete data deliverables partnering with software engineers applied scientists and business intelligence engineers
- Use GenAI tools to automate pipeline operations and accelerate your own development workflows

A day in the life
You might start the day checking pipeline health and fixing a data freshness issue before anyone downstream notices. Mid-day you define the data contract for events a new associate-facing feature will emit so the data arrives documented and usable. You close the day proposing a simplification to a legacy pipeline. Your stakeholders are software engineers applied scientists and business intelligence engineers; your customers are the customer service associates whose tools improve because of what your data reveals.

About the team
We are a multidisciplinary team of data engineers and scientists within the Associate Experience organization in Amazon Customer Service. Our organization builds the technology customer service associates use every day: the contact handling workspace AI-assisted resolution tools and the systems that measure service quality. Our team owns three connected charters: data engineering for the entire organization contact routing for driver support experiences and the science and AI capabilities that power both. As a data engineer here you will sit alongside scientists and build the datasets that engineering science and operations teams rely on.

- 3 years of data engineering experience
- 2 years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 3 years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- Bachelors degree or foreign equivalent in Computer Science Engineering Information Systems Mathematics or a related field
- 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 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
- Experience with data modeling warehousing and building ETL pipelines

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Seattle - 132100.00 - 178800.00 USD annually