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Data Engineer II

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Job Description

Job Description

The Digital Workplace Data & Analytics Platform with AI ML capabilities aims to bring together the data from all Unified Workspace, Collaboration and Colleague Servicing platforms, combining this with HR, Information Security, and network data to provide real-time, meaningful insights in areas such as user experience, health scoring, productivity, and overall IT visibility. As the Engineer 2 of the Digital Workplace Data & Analytics Platform, you will have responsibility for leading the engineering teams to develop the Advance Data engineering pipeline, Data Management, Data DevOps on Cloud platform and enhance it to provide personalization capabilities, analytics, and engineering automations, and best practices.

Our winning aspiration is to deliver the best Colleague digital experience. We simplify work and raise productivity by empowering Colleagues with the best digital tools and services.

Opportunity for Impact

Digital Workplace at American Express is entering into a new phase of technology transformation driven by opportunities to improve Colleague experience, raise productivity and collaboration, and drive operational efficiency of all service and infrastructure operations. If you have the talent and desire to deliver innovative products and services at a rapid pace, with hands on experience and strategic thinking, in areas of productivity and collaboration software suites, endpoint computing and security, mobile platforms, data management and analytics, and software engineering, join our leadership team to help with our transformation journey.

Responsibilities

The Data & Analytics platform with AI ML capabilities is central to the future of how we work and improve colleague experience while identifying opportunities for improvement.

As The Engineer Of This Group, You Will

  • Design and develop reusable Python-based frameworks for batch and real-time data ingestion from APIs, files, event streams, webhooks, and messaging systems.
  • Build scalable data pipelines on Google Cloud Platform using cloud-native services and modern distributed data processing technologies.
  • Develop reliable, observable, production-grade data pipelines with strong monitoring, auditing, lineage, and operational excellence.
  • Build reusable libraries and platform components that simplify data onboarding, transformation, orchestration, and pipeline lifecycle management.
  • Develop data quality, schema validation, and metadata-driven ingestion capabilities to improve platform reliability.
  • Build cloud-native microservices and APIs using Python for exposing data services and platform capabilities.
  • Develop containerized applications using Docker and deploy services on Kubernetes/GKE.
  • Contribute to platform observability using logging, monitoring, metrics, dashboards, and alerting.
  • Collaborate with architects, product owners, data engineers, ML engineers, and business teams to build scalable enterprise data platforms.
  • Participate in architecture discussions, code reviews, technical design, and engineering best practices.
  • Continuously improve engineering standards through automation, reusable frameworks, CI/CD, testing, and infrastructure as code.
  • A portfolio showcasing previous Cloud based Data & Analytics projects, contributions to open-source projects, or relevant publications is a plus.
  • Build culture of innovation, ownership, accountability, and customer focus
  • Contribute to the American Express Data & Analytics Strategy. Working with other Technology teams to drive enterprise solutions, define best practice at a company level and further develop skills and experience outside Digital Workplace.
  • Strengthen the collaboration with Industry partners/suppliers for more robust data solutions and market research for innovative solutions in this space.

Qualifications

Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline with 3+ years of experience in software or data engineering.
  • Strong proficiency in Python and SQL, with experience designing and developing scalable, reusable, and production-grade applications.
  • Hands-on experience building batch and real-time data pipelines using APIs, files, event streams, or messaging systems.
  • Experience with cloud platforms (GCP preferred) and cloud-native technologies including Docker, Kubernetes, CI/CD, and Git.
  • Good understanding of distributed data processing, data modeling, data quality, and data engineering best practices.
  • Experience developing RESTful APIs, microservices, or reusable platform components with a focus on scalability, reliability, and observability.
  • Strong problem-solving, communication, and collaboration skills with the ability to work effectively in an Agile environment.

Preferred Qualifications

  • Experience building reusable data ingestion, orchestration, or data quality frameworks for enterprise-scale data platforms.
  • Hands-on experience with GCP services such as BigQuery, Pub/Sub, GCS, GKE, Cloud Run, or equivalent cloud technologies.
  • Experience with Apache Spark, Kafka, Airflow (or similar orchestration tools), Elasticsearch/Kibana, and modern data engineering ecosystems.
  • Exposure to data visualization tools like Tableau, PowerBI, Grafana etc.
  • Knowledge of metadata management, data catalog, data lineage, semantic data models, or data governance concepts.
  • Experience implementing authentication and authorization (OAuth2, JWT, IAM), monitoring, logging, and observability for production systems.
  • Exposure to infrastructure as code, DevOps practices, and AI/ML data platform technologies is a plus.

Ideal Candidate Profile

The ideal candidate is a software engineer who enjoys building engineering platforms rather than one-off pipelines. They are comfortable designing reusable Python frameworks, building cloud-native services, and developing reliable distributed data systems. They have a strong ownership mindset, enjoy solving platform-scale problems, and are passionate about improving developer productivity through reusable tooling and automation.

About Us

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

About The Team

We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:

  • Competitive base salaries
  • Bonus incentives
  • Support for financial-well-being and retirement
  • Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location)
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
  • Generous paid parental leave policies (depending on your location)
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counseling support through our Healthy Minds program
  • Career development and training opportunities

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law.

Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.

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Job ID: 152081593

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