Job Description
Join American Express and be part of a global team that’s revolutionizing the way financial services are built and delivered. We’re looking for a passionate Data Engineer I to help us accelerate financial innovation by enabling rapid creation and iteration of banking products and services. At American Express, your contributions matter. You’ll be part of a dynamic, inclusive culture where your voice is heard and your work is valued.
As a Data Engineer I, you will play a critical role in shaping the architecture and data engineering workflows that power our modern banking platform. This position offers an exciting opportunity to solve real-world business challenges using leading-edge tools, frameworks, and agile methodologies.
Key Responsibilities
- Develop, test, and maintain high-quality software and data applications
- Collaborate in Agile teams to analyze user stories, design and develop applications, and automate tests
- Refactor code continuously to improve structure and maintainability
- Document technical and business requirements, ensuring alignment with data architecture
- Build and maintain data ingestion pipelines, schema, and metadata processes
- Lead or contribute to peer reviews and team-wide best practices
- Troubleshoot distributed storage and compute challenges
- Work with cross-functional teams to meet business data requirements
- Contribute to scalable, real-time data ingestion using Kafka-based pipelines
- Apply Test Driven Development (TDD) principles throughout the software lifecycle
Required Qualifications
- Bachelor’s degree in Computer Science, Information Technology, or a related field
- Experience in Python Object-Oriented Programming and dependency management using Poetry
- Strong command of built-in Python libraries (e.g., JSON, Base64, os, logging)
- Proficiency in asynchronous microservices using FastAPI
- Experience with distributed data frameworks, especially PySpark (DataFrames, Spark SQL)
- Knowledge of Cornerstone Ingestion Processes and Business Metadata
- Familiarity with Yellowbrick for interactive analytics
- Hands-on experience with Hyperdrive JSON schema and Kafka-based real-time ingestion pipelines
- Understanding of Event Engine Management and Amex logging framework
- Sound knowledge of data governance tools like Collibra and Manta
- Experience working with REST API specifications (Swagger)
- Familiarity with CI/CD tools like Jenkins, Development Tool Central, and XLR
- Containerization skills using Docker and Kubernetes (PODs)
- Experience in cloud deployment and monitoring using Hydra
- Domain knowledge in banking processes such as Zelle, ACH, and Intraday Money Movement
- Strong analytical, problem-solving, and communication skills
Preferred Attributes
- Ability to work independently and manage multiple tasks simultaneously
- Strong sense of initiative and ownership
- Adaptable to change and open to experimentation
- Effective at communicating complex technical concepts to non-technical stakeholders
- Organized, self-driven, and detail-oriented
Benefits and Perks
- Competitive base salary with performance-based bonuses
- Flexible hybrid work environment
- Retirement savings support and financial planning tools
- Comprehensive healthcare (medical, dental, vision, disability, life insurance)
- Generous paid parental leave and wellness benefits
- On-site wellness centers at select locations
- Free and confidential mental health counseling via Healthy Minds program
- Continuous learning and career development opportunities
Eligibility
- Education: Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field
- Batch: Graduates from 2021, 2022, 2023, 2024 are eligible to apply
Technical Skills (comma-separated):
Python, FastAPI, PySpark, Spark SQL, JSON, Base64, Kafka, Hyperdrive, Yellowbrick, Event Engine, Poetry, Jenkins, Collibra, Manta, Swagger, Docker, Kubernetes, Hydra, Agile, TDD, REST APIs, CI/CD, Logging Frameworks, Cornerstone, Data Ingestion, Data Governance, Microservices Architecture
Education Requirements
Eligible Batch Years
