Remote Data Engineer Opportunity at American Express ($27/Hour)
We're excited to announce an immediate opening for a skilled Data Engineer to join our team at American Express. As a key member of our tech group, you'll have the opportunity to design, code, and deploy software that makes a significant impact on our clients' digital lives.
Job Details:
Location: Remote (Arizona, USA)
Company: American Express
Compensation: $27/hour
Position: Data Engineer
Employment Type: Full-time
Work Hours: 8 hours/day
About the Role:
As a Data Engineer at American Express, you'll be responsible for building core features and components of card transaction systems on a distributed platform deployed in a hybrid cloud environment. You'll work closely with experienced architects in an open, collaborative, and inclusive environment where your voice is valued, and you have the autonomy to make technical decisions.
Responsibilities:
Design and build distributed data processing and analytics systems
Develop high-level and detailed designs of subsystems/features with a focus on performant code
Collaborate with engineers on daily activities and contribute to code and SDLC tasks
Build proof-of-concepts to validate new ideas and technologies
Stay up-to-date with industry-leading technologies and solutions
Foster a culture of innovation and experimentation, and collaborate with cross-functional teams
Requirements:
2+ years of experience in software design and implementation using Java or Scala
Experience with data processing using Apache Spark
Knowledge of designing, implementing, and operating NoSQL databases like Cassandra or Elasticsearch
Preferred Qualifications:
Experience with distributed data processing and analytics using Cassandra, Elasticsearch, or Apache Spark
Experience with distributed messaging systems like Kafka
Experience with building microservices and Service Mesh
Experience with cloud platforms like Docker, Kubernetes, or OpenShift
Experience with Continuous Integration, Continuous Delivery, and DevOps frameworks
What We Offer:
A competitive salary, opportunities for professional growth and development, and a collaborative and inclusive work environment.
Ready to join our team? Apply Now or learn more about this opportunity.
Apply Now
Job Details:
Location: Remote (Arizona, USA)
Company: American Express
Compensation: $27/hour
Position: Data Engineer
Employment Type: Full-time
Work Hours: 8 hours/day
About the Role:
As a Data Engineer at American Express, you'll be responsible for building core features and components of card transaction systems on a distributed platform deployed in a hybrid cloud environment. You'll work closely with experienced architects in an open, collaborative, and inclusive environment where your voice is valued, and you have the autonomy to make technical decisions.
Responsibilities:
Design and build distributed data processing and analytics systems
Develop high-level and detailed designs of subsystems/features with a focus on performant code
Collaborate with engineers on daily activities and contribute to code and SDLC tasks
Build proof-of-concepts to validate new ideas and technologies
Stay up-to-date with industry-leading technologies and solutions
Foster a culture of innovation and experimentation, and collaborate with cross-functional teams
Requirements:
2+ years of experience in software design and implementation using Java or Scala
Experience with data processing using Apache Spark
Knowledge of designing, implementing, and operating NoSQL databases like Cassandra or Elasticsearch
Preferred Qualifications:
Experience with distributed data processing and analytics using Cassandra, Elasticsearch, or Apache Spark
Experience with distributed messaging systems like Kafka
Experience with building microservices and Service Mesh
Experience with cloud platforms like Docker, Kubernetes, or OpenShift
Experience with Continuous Integration, Continuous Delivery, and DevOps frameworks
What We Offer:
A competitive salary, opportunities for professional growth and development, and a collaborative and inclusive work environment.
Ready to join our team? Apply Now or learn more about this opportunity.
Apply Now