Senior Engineer - Commercial Data Engineering

You Lead the Way. We’ve Got Your Back.

With the right backing, people and businesses have the power to progress in incredible ways. When you join Team Amex, you become part of a global and diverse community of colleagues with an unwavering commitment to back our customers, communities and each other. Here, you’ll learn and grow as we help you create a career journey that’s unique and meaningful to you with benefits, programs, and flexibility that support you personally and professionally.

At American Express, you’ll be recognized for your contributions, leadership, and impact—every colleague has the opportunity to share in the company’s success. Together, we’ll win as a team, striving to uphold our company values and powerful backing promise to provide the world’s best customer experience every day. And we’ll do it with the utmost integrity, and in an environment where everyone is seen, heard and feels like they belong.

Join Team Amex and let's lead the way together.

As part of our diverse tech team, you can architect, code and ship software that makes us an essential part of our customers’ digital lives.  Here, you can work alongside talented engineers in an open, supportive, inclusive environment where your voice is valued, and you make your own decisions on what tech to use to solve challenging problems.  American Express offers a range of opportunities to work with the latest technologies and encourages you to back the broader engineering community through open source.  And because we understand the importance of keeping your skills fresh and relevant, we give you dedicated time to invest in your professional development.  Find your place in technology on #TeamAmex.

We’re looking for an experienced senior data engineer to join our Commercial Data Engineering organization. We build data-centric solutions to support the Global Commercial Services product suite including B2B payments, large corporate clients, and our small and medium enterprise ecosystem. You’ll will part of the team that builds innovative, scalable, resilient data systems that enable us to unlock the value of our data for all of our products. 

How will you make an impact in this role?

Responsible for working on data engineering architecture, solutioning and ETL pipelines.

• Play a critical role in the development, design, and maintenance of large-scale distributed data platform.
• Build and maintain reliable, efficient data pipelines using airflow and spark. 
• Help facilitate sprint planning, daily scrum, sprint review and sprint retrospective. 
• Work closely with the Product team and stake holders and understand the business requirements and deliver the features. 
• Analyze complex data systems and the flow, relationships, and dependencies of our data to contribute to conceptual, logical, and physical data models. 
• Provide support for consumers of our data platform and educate them on best practices for utilizing our data platform to solve business problems. 
• Responsible for providing on-call support on a rotation basis and troubleshoot failed jobs if any and try to resolve the issues. 
• Tune and optimize spark jobs for maximum efficiency and minimum latency. 
• Ensure high data quality and implement processes to detect and correct data inconsistencies. 
• Implement data security measures ensuring compliance with company’s standards. 
• Stay up to date with advances in big data technologies. 

Minimum Qualifications

• Bachelor’s in Computer Science/Engineering and 8+ years of equivalent experience in related disciplines. 
• At least 8 years of experience in Abinitio, 5 Plus of experience in big data technologies such as Spark and workflow orchestration tool like Airflow. 
• Proficiency in programming languages such as Scala, Python with at least 5 years of experience. 
• Deep understanding of ETL Processes and experience in sql and nosql databases. 
• Hands on experience in building and maintaining BigData Pipelines. 
• Hands on experience with CI/CD processes.  
• Hands on experience providing oncall support on rotation basis.

Preferred Qualifications

• Experience working in code conversions from Abinitio to Spark.
• Experience in data migration from databases to data lakes.
• Experience in creating reusable libraries and data frameworks.

Salary Range: $110,000.00 to $190,000.00 annually + bonus + benefits

The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors.

We back our colleagues and their loved ones with benefits and programs that support their holistic well-being. That means we prioritize their physical, financial, and mental health through each stage of life. Benefits include:

• Competitive base salaries 
• Bonus incentives 
• 6% Company Match on retirement savings plan 
• Free financial coaching and financial well-being support 
• Comprehensive medical, dental, vision, life insurance, and disability benefits 
• Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need 
• 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy 
• 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

For a full list of Team Amex benefits, visit our Colleague Benefits Site.

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.

We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.

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