Company Name:-
American Express

Job Location:-
Gurgaon, Haryana

Job Summary:-
You Lead the Way.

We’ve Got Your Back.

At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways.

Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way.

When you join #TeamAmex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day.

Function Description:
If you have a strong will to learn and educate and are motivated by the opportunity to help grow our team and be a part of an industry-leading technology and innovation organization, then look no further! This is an opportunity to lead the Technology Enterprise Data Quality & Analytics Engineering while heavily influencing the Enterprise Data Management, as well as a series of Enterprise Technology capabilities (e.

g.

AI/ML, Big Data, Cloud, Real-Time Event Processing & Analytics, etc.

) to support the end-to-end development and execution of Amex’s data management strategy, and to drive engineering excellence.

You will be solving very interesting problems that directly and greatly impact hundreds of millions of individuals worldwide .

There are hundreds of opportunities to make your mark on technology and life at American Express.

This role within American Express Technology (AET) will report into the leader overseeing Enterprise Data Architecture, Enterprise Machine Learning Engineering, Enterprise Real-Time Event Processing and Analytics Platform, as well as Chairing the Technology Risk Model Committee.

Responsibilities:
Partner with business, product, and engineering teams to unlock the power of leveraging data across Amex.

Drive the vision, strategy, and implementation of Enterprise Data Quality capabilities, to enable Data Quality as a Service (DQaaS) on-premises and on Cloud.

Lead the Implementation of data quality and controls for identifying and mitigating any data quality risks across key operational business processes and decision making.

Partner with Enterprise Data Architecture in the

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