Data Engineer, OIS/CXI Analytics

Data Engineer on the OIS/CXI Analytics team, onsite in Nashville, TN, will build scalable data pipelines and ML-ready data infrastructure to power AI-driven operational insights across Amazon's fulfillment and operations networks; salary range USD 125,500 - 169,800 per year.

Responsibilities

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

Requirements

• At least three years of data engineering experience.
• A minimum of three years designing and managing large-scale data architectures for BI analytics, supported by data modeling experience.
• Proficiency in data modeling, data warehousing, and constructing ETL pipelines.
• Experience with AWS services including Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.
• Experience in data warehouse architectures, data modeling, infrastructure components, ETL/ELT processes, reporting/analytics tools and environments, data structures, and hands-on SQL coding.
• Bachelor's degree or higher in computer science, engineering, machine learning, 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 tools such as CDK or CloudFormation, and CI/CD pipelines for data and ML systems.
• Experience in data modeling and relational as well as non-relational database design.

Technologies

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

Benefits

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

Preferred Qualifications

• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Master's degree or above in computer science, engineering, analytics, mathematics, statistics, IT or equivalent