Data Engineer

Amazon.com Services LLC is seeking a Data Engineer to design scalable data pipelines and ML-ready infrastructure that enable GenAI-powered analytics across its Operations Technology ecosystem. This onsite role in Austin, TX focuses on delivering robust data platforms that support global operations and data-driven decision making. The position offers an annual salary range of USD 125,500 to 178,800.

Responsibilities

• Design, implement, and maintain production-grade ETL/ELT pipelines and scalable big data infrastructure that underpin Operations Technology operational intelligence.
• Develop feature engineering workflows and ML-ready data pipelines to support data science experimentation and production model serving.
• Contribute to data governance and quality standards across analytical and ML data products.
• Assist in deploying GenAI solutions for automated reporting, diagnostics, predictive, and prescriptive analytics.
• Build and maintain semantic layers and dashboard data models that inform global operations decisions.
• Collaborate with Program Managers, BI teams, ML Engineers, Data Scientists, and operational stakeholders to prioritize work aligned with OTS goals.
• Adhere to and contribute to data engineering best practices, including code reviews, testing, monitoring, and documentation.

Requirements

• At least 3 years of data engineering experience.
• At least 3 years of developing and operating large-scale data structures for business intelligence analytics with data modeling experience.
• Experience in data modeling, data warehousing, and building ETL pipelines.
• Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.
• Background in data warehouse architectures, data modeling, infrastructure components, ETL/ELT processes, reporting and analytic tools, data structures, and hands-on SQL coding.
• Bachelor’s degree or higher 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

Benefits

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