Data Engineer

Data Engineer at Amazon.com Services LLC onsite in Austin, TX offers the opportunity to build scalable data pipelines and ML ready infrastructure that enable GenAI powered analytics across Amazon's Operations Technology ecosystem. The role provides a competitive salary range and on-site collaboration in a dynamic environment. Salary: USD 125,500 - 178,800 per year. Location: Austin, TX.

Benefits

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

Role overview

The Data Engineer will design, build, and maintain production grade ETL and ELT pipelines alongside big data infrastructure that underpins operational intelligence for the Operations Technology stack. You will create ML ready data pipelines and feature engineering workflows to support Data Science experimentation and production model serving. You will contribute to data governance and quality standards and help implement GenAI driven reporting, diagnostics, predictions, and prescriptive analytics. You will also shape semantic layers and dashboard data models that guide global operations decisions, collaborating with program managers, BI teams, ML engineers, data scientists, and operational stakeholders to align work with OTS goals.

Responsibilities

• Design, build, and maintain production grade ETL/ELT pipelines and big data infrastructure supporting OTS operational intelligence.
• Develop feature engineering workflows and ML ready data pipelines for experimentation and production model serving.
• Contribute to data governance and quality standards across analytical and ML data products.
• Support the implementation of GenAI solutions for automated reporting, diagnostics, predictive, and prescriptive analytics.
• Build and maintain semantic layers and dashboard data models that power worldwide operations decisions.
• Partner with Program Managers, BI teams, ML Engineers, Data Scientists, and operational stakeholders to prioritize work aligned with OTS goals.
• Follow and contribute to best practices for data engineering, including code reviews, testing, monitoring, and documentation.

Requirements

• 3+ years of data engineering experience
• 3+ years developing and operating large-scale data structures for business intelligence analytics using data modeling experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions
• Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
• Bachelor's degree or above in computer science, machine learning, engineering, or related fields, or equivalent experience building and maintaining data flows and pipelines
• Proficiency in Python and SQL; experience with PySpark or Apache Spark
• Experience with infrastructure as code (CDK, CloudFormation) and CI/CD pipelines for data and ML systems
• Experience with data modeling and relational/non-relational database design

Technologies

• Redshift
• S3
• AWS Glue
• EMR
• Kinesis
• FireHose
• Lambda
• IAM
• Python
• SQL
• PySpark
• Apache Spark
• CDK
• CloudFormation