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# Data Engineer, OIS/CXI Analytics

- **Company:** Amazon.com, Inc.
- **Location:** Nashville, TN, United States
- **Experience:** Experienced
- **Salary:** $125,500.0 - $178,800.0
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon S3, Business Analytics Applications, Data Analysis, Big Data, Code Review, Databases, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Structures, Data Stores, Data Warehousing, Graph Database, Identity and Access Management, Python (Programming Language), Machine Learning, Standard Sql, SQL Databases, Data Streaming, Systems Architecture, Management of Software Versions, Feature Engineering, Apache Spark, Electronic Medical Records, Cloudformation, Pyspark, Information Technology, AWS Glue, Non-relational Database, Machine Learning Operations, Data Pipelines, Amazon Redshift
- **Published:** May 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c8b8e3e75bb120d4

## About the Role

Do you have experience in Systems architecture within technology?, * 3+ years of data engineering experience

 * 3+ years of 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 like 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 experience including, 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 systemsExperience with data modeling and relational/non-relational database design, * 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

## Description

Join the OIS/CXI Analytics team to build strategic data infrastructure powering Amazon's Operations Technology ecosystem. Our team provides critical data infrastructure support for OpsTech IT, supporting Amazon's global customer commitment. You'll work at the intersection of large-scale data processing and real-world operational impact - creating intelligence that directly influences how Amazon fulfills millions of orders across fulfillment centers, Amazon Fresh, Prime Now, Lockers, Pantry, and Amazon Campus.

As a Data Engineer, you will build and maintain scalable data pipelines and ML-ready data infrastructure that power AI-driven operational insights and Data Science initiatives across Amazon's global fulfillment and maintenance networks. You will design and implement ETL/ELT pipelines, build feature engineering workflows, and partner with ML Engineers, Data Scientists, Applied Scientists, and BIEs to deliver data products that drive measurable business outcomes. You will contribute to MLOps data practices - including data versioning, pipeline monitoring, and model retraining data support - and help establish engineering best practices within the team. You will support Data Science teams by building curated, analysis-ready models and datasets and enabling self-service data access through well-governed data infrastructure. This role directly enables the team's mission to implement GenAI solutions for automated reporting, diagnostics, and predictive and prescriptive analytics across
worldwide operations.

This is a high-impact individual contributor role with significant opportunity to grow technical scope and organizational influence at the intersection of data engineering, Data Science, and AI., * Design, build, and maintain production-grade ETL/ELT pipelines and big data infrastructure supporting OTS operational intelligence.

 * Build feature engineering workflows and ML-ready data pipelines that support Data Science experimentation and production model serving.
 * Contribute to data governance and quality standards across analytical and ML data products.
 * Support implementation of GenAI solutions for automated reporting, diagnostic, predictive, and prescriptive analytics.
 * Build and maintain semantic layers and dashboard data models that power worldwide operations business decisions.
 * Partner with Program Managers, BI teams, ML Engineers, Data Scientists, and operational stakeholders to prioritize work aligned with OTS business goals.
 * Follow and contribute to best practices for data engineering, including code reviews, testing, monitoring, and documentation.


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