> Markdown version of [/jobs/ext/2610572-data-engineer-marketplace](https://www.wearedevelopers.com/jobs/ext/2610572-data-engineer-marketplace). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer, Marketplace - **Company:** Amazon.com, Inc. - **Location:** Austin, TX, United States - **Experience:** Experienced - **Salary:** $132,100.0 - $178,800.0 - **Contract:** Permanent contract - **Skills:** Abstraction Layers, Amazon Web Services, Amazon S3, Databases, Information Engineering, Extract Transform Load (ETL), Data Structures, Data Stores, Graph Database, Identity and Access Management, Data Ingestion, Electronic Medical Records, AWS Glue, Non-relational Database, Marketplace, Amazon Redshift - **Published:** August 6, 2026 - **Apply:** https://www.amazon.jobs/en/jobs/10496061/data-engineer-marketplace ## About the Role 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines Preferred Qualifications - 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) ## Description The Data Engineer will design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for analytics. Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes leveraging AWS technologies and data tools. Provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources. Produce comprehensive, usable dataset documentation and metadata. Provides input and recommendations on technical issues. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [In-Memory Computing - The Big Picture](https://www.wearedevelopers.com/videos/626-in-memory-computing-the-big-picture) - [Tips, Techniques, and Common Pitfalls Debugging Kafka](https://www.wearedevelopers.com/videos/838-tips-techniques-and-common-pitfalls-debugging-kafka) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 162: AI careers, MCP, AWS best practices & floppy sweaters](https://www.wearedevelopers.com/magazine/571-dev-digest-162-ai-careers-mcp-aws-best-practices-floppy-sweaters) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)