Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, metro location, and generalist engineering-manager title drive high candidate competition.
Strong ML/data engineering focus increases domain bias, though managerial full-stack skills remain somewhat transferable.
Explicit 10+ years plus specific ML/data, full-stack, and tech-stack requirements create high shortlisting strictness.
Lead strategic technical direction and development processes for Analytics & AI applications within Mastercard Services.
Manage and mentor a cross-functional engineering team to deliver scalable, data-driven AI products and features.
Collaborate with product and design teams to define roadmaps, scope, and ensure projects meet customer demands and scalability needs.
10+ years of engineering experience in an agile production environment.
Proficiency in object-oriented programming (Java/Spring preferred), front-end frameworks (React with Redux, Typescript), Git, Jenkins, RESTful APIs, SQL, and multi-threading.
Experience with data-driven applications, data pipelines, machine learning systems at scale using Java, Scala, or Python.
Degree in Computer Science or related technical field.
Experienced leader comfortable managing full-stack engineering teams building AI and analytics solutions in agile settings.
Strong technical expertise spanning backend, frontend, and data engineering with cloud-native microservices and streaming technologies (Kafka, Zookeeper) considered a plus.
Collaborates effectively across multiple teams and geographies, driving innovation, accountability, and continuous improvement.