Senior Backend Software Engineer (Python) at Mastercard

Ramat Gan, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

08 Aug, 26

Salary

0.0

Posted On

10 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Java, Go, AWS, GCP, Azure, Docker, Kubernetes, SQL, NoSQL, Terraform, CloudFormation, CI/CD, Microservices, MLOps, Distributed Systems

Industry

technology;Information and Internet

Description

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Backend Software Engineer (Python) Overview: Dynamic Yield by Mastercard is seeking a backend engineer with a strong foundation in building scalable, high-performance systems and a deep understanding of cloud infrastructure, distributed systems, and data pipelines. This role focuses on designing and optimizing backend services that support our machine learning (ML) operations and real-time personalization capabilities. We foster a professional environment where experienced engineers collaborate to drive technical excellence, continuously improving our backend architecture and infrastructure. As a Backend Engineer, you will play a key role in building and maintaining the backend services that power our ML infrastructure, ensuring efficiency, scalability, and reliability. Role & Responsibilities: Design, develop, and optimize backend services that support ML pipelines, APIs, and real-time decision-making systems. Architect and implement scalable and reliable data processing workflows, integrating ML models into production environments. Build and maintain infrastructure for efficient model deployment, monitoring, and versioning. Ensure high availability, performance, and security of backend services. Lead initiatives to improve system architecture, reduce technical debt, and enhance development processes. Collaborate with data scientists, ML engineers, and DevOps teams to streamline ML model integration. Stay up to date with the latest advancements in backend technologies, cloud computing, and distributed systems. Qualifications & Experience: 4+ years of experience in backend engineering, designing and developing distributed systems. Strong proficiency in Python (preferred), Java, or Go for backend development. Deep experience with cloud platforms (AWS, GCP, or Azure), including compute, storage, and networking services. Experience with containerization and orchestration (Docker, Kubernetes). Proficiency in designing and managing scalable databases (SQL & NoSQL: MySQL, PostgreSQL, Redis, Cassandra, etc.). Hands-on experience with CI/CD pipelines, infrastructure as code (Terraform, CloudFormation), and automated deployments. Familiarity with high-performance APIs and microservices architecture. Experience working with ML operations (MLOps) and data pipelines is a plus but not required. 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. Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.

Responsibilities

Design and optimize backend services and data pipelines to support machine learning operations and real-time personalization. Lead initiatives to improve system architecture, ensure high availability, and collaborate with cross-functional teams for model integration.