> Markdown version of [/jobs/ext/3928031-senior-data-engineer-ii-amex-ads-offers-and-dining-technology](https://www.wearedevelopers.com/jobs/ext/3928031-senior-data-engineer-ii-amex-ads-offers-and-dining-technology). 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).

---

# Senior Data Engineer II - Amex Ads, Offers, and Dining Technology

- **Company:** American Express Company
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $123,000.0 - $215,250.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon S3, Data Analysis, Business Software, Cloud Database, Information Systems, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, Dimensional Modeling, Python (Programming Language), Performance Tuning, Query Optimization, Software Engineering, SQL Databases, Enterprise Data Management, Data Processing, Snowflake, Git, Data Layers, Data Lakes, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Data Pipelines
- **Published:** October 26, 2026
- **Apply:** https://www.manhattanjobs.com/job.asp?id=3472138108&tx=CT3735TTD&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field.
 * 8+ years of experience in Data Engineering, Software Engineering, or Enterprise Data Platforms.
 * Strong hands-on expertise in:

o Snowflake

o SQL and advanced query optimization

o Python

 * ETL/ELT pipeline development and orchestration
 * Experience designing and implementing scalable data pipelines and cloud-based data integration solutions.
 * Strong understanding of data warehousing concepts, dimensional modeling, and modern data lake/lakehouse architectures.
 * Experience implementing data quality frameworks, reconciliation processes, schema evolution handling, and production monitoring.
 * Familiarity with CI/CD pipelines, Git, Infrastructure as Code, and automated deployment practices.
 * Excellent problem-solving, communication, stakeholder management, and cross-functional collaboration skills.
 * Proven ability to lead end-to-end delivery of enterprise-scale data engineering initiatives across multiple teams.

Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions

## Description

* Lead the design, development, and implementation of scalable data pipelines and data architecture to support dining analytics, reporting, and downstream business applications.
 * Build and maintain reliable batch and incremental ETL/ELT workflows, including ingesting Rooam POS data from AWS S3 into Snowflake and transforming it into analytics-ready datasets.
 * Design and optimize Snowflake data models, including staging, curated, and business-ready data layers to support reporting, analytics, and operational use cases.
 * Develop scalable data processing solutions using Python, SQL, and AWS cloud services while ensuring performance, reliability, and maintainability.
 * Implement data quality validation, reconciliation, monitoring, and alerting to ensure the accuracy, completeness, and timeliness of Rooam POS data.
 * Partner with Product, Business, Analytics, Architecture, and Engineering teams to define data requirements and deliver scalable data solutions.
 * Drive performance optimization across Snowflake by tuning SQL queries, optimizing storage strategies, and managing compute resources efficiently.
 * Lead technical design discussions, mentor engineers, and promote engineering best practices across data engineering initiatives.
 * Strengthen platform reliability through automation, CI/CD, observability, documentation, and operational excellence.
 * Support enterprise data governance by maintaining metadata, documentation, lineage, and secure access to data assets.