Our team within Mastercard - Data & Services:
The Data & Services team is a key differentiator for Mastercard, providing the cutting-edge services that are used by some of the world's largest organizations to make multi-million dollar decisions and grow their businesses. Focused on thinking big and scaling fast around the globe, this agile team is responsible for end-to-end solutions for a diverse global customer base. Centered on data-driven technologies and innovation, these services include payments-focused consulting, loyalty and marketing programs, business Test & Learn experimentation, and data-driven information and risk management services.

Advance Analytics Program:
Within the D&S Technology Team, the Advance Analytics program is a program that is comprised of a rich set of products that provide accurate perspectives on Portfolio Optimization, Acquire Optimizer, Test & Learn, Credit Risk, and Ad Insights. Currently, we are enhancing our customer experience with new user interfaces, moving to API-based data publishing to allow for seamless integration in other Mastercard products and externally, utilizing new data sets and algorithms to further analytic capabilities, and generating scalable big data processes.

Position Responsibilities:
We are looking for an experienced and innovative Software - Data Engineering to develop AI/ML , Big Data solutions as Paas Platform.
As a Data Engineer - Software Engineer, you will:
• Participate in scoping, design and implementation of complex features
• Understand Design and Implement intuitive, responsive UIs that allow Customers to better understand data and analytics
• Ensure a high-quality code base by writing high performant, well-tested code
• Drive innovative improvements to team development processes
• Partner with Product Managers and Customer Experience Designers to understand and implement use cases and apply that knowledge to scoping and building new modules and features
• Collaborate across teams with exceptional peers who are passionate about what they do

Ideal Candidate Qualifications:
• 3+ years of full stack engineering experience in an agile production environment
• Experience development and implementation of large, complex features in full-stack applications
• Experience leveraging open source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform analyses
• High proficiency in using Python and/or Scala, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi, Scoop), SQL to build Big Data products & platform
• Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale in Java, Scala, or Python and deliver analytics involving all phases like data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting
• Proficiency with Java/Spring Boot, and / or .NET/C# and SQL Server, front-end frameworks, and/or relational database technologies
• Good to have understanding of React, Redux, Typescript
• Strong technologist with proven track record of learning new technologies and frameworks
• Customer-centric development approach
• Passion for analytical / quantitative problem solving
• Collaboration skills with experience working with people across roles and geographies
• Superior academic record with a degree in Computer Science or related technical field
• Strong written and verbal English communication skills

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard's security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.