# Senior Data Engineer, WW Ops Finance - S&A at Amazon

Amazon is hiring a Senior Data Engineer, WW Ops Finance - S&A. It pays $155k-$209k a year and Level rates it Little AI ●○○○; you can [apply on Amazon](https://jobsbylevel.com/go/63780124-0e3c-4f7f-a756-c8a35577ae03?utm_medium=ai-agent).

AI Level 1, AI centrality 30 out of 100. US, TX, Irving.

## Details

- Company: [Amazon](https://jobsbylevel.com/companies/amazon)
- AI level: AI Level 1 (score 30 out of 100)
- Location: US, TX, Irving
- Salary: $155k-$209k
- Posted: November 12, 2026
- Apply: https://jobsbylevel.com/go/63780124-0e3c-4f7f-a756-c8a35577ae03?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=senior-data-engineer-ww-ops-finance-s-a-at-amazon-bae40d

## Prepare for this job

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## Description

Are you passionate about standardizing data platforms and automating data engineering to drive analytics and reporting? Do you excel in dynamic, fast-paced environments and find joy in converting data into actionable insights? Are you adept at implementing data governance practices and defining data access and quality standards? If you thrive in innovation and can deliver scalable Data Engineering Solutions, then the Worldwide Operations Finance Standardization & Automation (SnA) team has an exciting opportunity for you! We are seeking a customer-centric Senior Data Engineer to establish a reliable and accessible data platform, ensuring Operations Finance customers have complete trust in the data, technology, and tools to make data-driven business decisions. As a Senior Data Engineer in WW S&A, you will be working in one of the world's largest and most complex data ecosystems. You will design, build, and own scalable data domains that serve as the foundational layer for the business. In this role, you will architect and implement robust, well-governed data domain models that integrate multi-heterogeneous data sources, enabling seamless consumption across a wide spectrum of use cases - including real-time and batch analytics, interactive dashboards and reporting, machine learning and predictive modeling, operational automation, API-driven data services, self-service exploration, and ad-hoc data requests. As a Sr. DE, you will define domain boundaries, establish data contracts, and curate high-quality, discoverable datasets that empower cross-functional teams to derive insights quickly and reliably, while ensuring data is aggregated, retrieved, and served in a fast, secure, and scalable manner across all consumption patterns. You should have excellent business and communication skills to be able to work with business owners, Product teams and Tech leaders to gather infrastructure requirements, design data infrastructure, build up data pipelines and data-sets to meet business needs. You will be responsible for designing, developing, and operating a data service platform using Python, Airflow, and SQL to build the various ETL, analytics, and data quality components. You’ll automate deployments using AWS CodeDeploy, AWS CodePipeline, AWS Cloud Development Kit (CDK), and AWS Cloud Formation. You will work with AWS services like Redshift, Glue, S3, IAM, CloudWatch, and more. Key job responsibilities Key job responsibilities - Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using Python, SQL and AWS big data technologies. - Explore and learn the latest AWS technologies to provide new capabilities and increase efficiencies of the team. Designing and implementing complex pipelines and other Data Engineering solutions. - Work closely with business owners, developers, Business Intelligence Engineer to explore new data sources and deliver the data. - Create extensible designs and easy to maintain solutions with the long term vision in mind - Improve tools, processes, scale existing solutions, create new solutions as required based on team and stakeholder needs - Familiar with AI Delivery Life Cycle (DLC), contributing to the end-to-end process of delivering AI-powered solutions - from ideation and data preparation through model development, deployment, monitoring, and iteration. Basic qualifications - 7+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL - Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS - Experience mentoring team members on best practices - Experience building data products incrementally and integrating and managing data sets from multiple sources Preferred qualifications - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience operating large data warehouses - Experience operating highly

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