Jobs at Mastercard

Lead and support complex Mastercard customer implementations across Europe from initiation through launch. Manage project plans, timelines, governance, risks, dependencies, and escalations while coordinating customers and cross-functional internal teams. Provide implementation guidance, assess product and operational impacts, support pilots and product launches, and improve delivery processes, documentation, and best practices. Serve as a trusted customer advisor, communicate with technical and business stakeholders, and contribute to training, mentoring, and knowledge sharing.

Provides senior individual-contributor technical leadership for complex, enterprise-scale software systems. Leads architecture, design, development, testing, deployment, operational readiness, and production issue resolution across distributed platforms. Partners with product, business, architecture, and engineering teams to deliver secure, scalable, resilient solutions; drives automation, engineering standards, technical roadmaps, reliability, performance, and developer productivity. Influences cross-functional initiatives, mentors engineers, and contributes to architecture forums and engineering communities.

Leads the design, development, deployment, and evaluation of machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, and partners with product, engineering, analytics, and business teams. Mentors data scientists and AI engineers, presents technical recommendations to leadership, supports hiring, and shapes the organization’s long-term technical direction.

Leads the design and implementation of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architects Databricks, Spark, Delta Lake, and cloud-based solutions; establishes data quality, governance, lineage, security, monitoring, and operational standards; modernizes legacy systems; optimizes large-scale processing; influences technical strategy; mentors engineers; and partners with cross-functional stakeholders to deliver resilient, compliant data products.

Monitor and respond to production alerts, troubleshoot distributed applications, improve reliability, and reduce recovery times. Support deployments and CI/CD pipelines across environments, implement automation, analyze ITSM activities, monitor service health, and participate in incident response and blameless postmortems. Collaborate with global development, operations, and product teams, identify resiliency gaps, optimize systems, and mentor junior team members while promoting DevOps standards and best practices.

Monitor and respond to production alerts, troubleshoot distributed web applications, improve reliability and system health, support deployments and CI/CD pipelines, automate operational processes, analyze ITSM activities, and lead incident response and blameless postmortems. Collaborate across development, operations, and product teams while mentoring junior resources and advancing DevOps standards and practices.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, measures business impact, partners with cross-functional stakeholders, presents findings to leadership, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the technical direction of the AI organization.

Lead the architecture, design, development, and modernization of Mastercard’s cloud-native experimentation and analytics platform. Build scalable services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and PySpark. Drive technical strategy, system design, code reviews, delivery, observability, security, and reliability across distributed teams while mentoring engineers and coordinating cross-functional initiatives.

Provides expert individual-contributor leadership for enterprise-scale software engineering. Designs and delivers secure, scalable, resilient distributed systems; drives architecture, development, testing, deployment, automation, observability, and operational excellence. Partners with product, business, architecture, and engineering teams to translate strategy into technical solutions, resolve complex production issues, reduce technical debt, and improve engineering practices. Influences technical roadmaps, mentors engineers, and promotes standards across teams and geographies.

Lead architecture, design, coding, testing, and delivery of scalable cloud-native software for Mastercard’s experimentation and analytics platform. Build distributed services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, and Spark. Drive modernization, technical strategy, architecture reviews, security, reliability, observability, and continuous delivery. Coordinate globally distributed teams, collaborate across engineering and business functions, and mentor engineers while championing engineering excellence.

Monitor and respond to production alerts, troubleshoot distributed applications, improve reliability and system health, support CI/CD deployments, automate operational processes, analyze ITSM activities, and conduct incident response and blameless postmortems. The role also collaborates globally across development, operations, and product teams while promoting DevOps standards and mentoring junior colleagues.

Monitor and respond to production alerts across web applications, troubleshoot distributed systems, and improve reliability and recovery times. Support deployments and CI/CD pipelines, automate operational processes, maintain service health, analyze ITSM activities, and provide feedback to development teams. The role also promotes DevOps standards, participates in incident response and blameless postmortems, mentors junior resources, and collaborates with global development, operations, and product teams.

Leads customer implementations of Mastercard products and services across Europe, managing onboarding, project plans, milestones, risks, dependencies, governance, and production readiness. Coordinates customers and cross-functional teams across product, technology, operations, and account management. Provides payments implementation expertise, supports launches and pilots, improves delivery processes, and contributes to documentation, training, mentoring, and knowledge sharing.

Leads the design and evolution of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architects cloud-based ETL/ELT, lakehouse, streaming, governance, and data quality solutions; modernizes legacy assets; optimizes processing; and establishes engineering standards, testing, deployment, and operational practices. Partners across risk, product, architecture, and engineering, influences technical direction, mentors engineers, supports compliance, and drives strategic roadmap execution.

Provides enterprise-scale software engineering leadership as a senior individual contributor. Leads architecture, design, development, testing, deployment, and operational excellence across secure, distributed systems. Translates business requirements into scalable solutions, drives technical standards and automation, resolves complex production issues, reduces technical debt, and influences engineering roadmaps. Partners across product, business, architecture, and engineering teams while mentoring engineers and promoting consistent engineering practices.

Lead and support complex Mastercard customer implementations across Europe from initiation through launch. Responsibilities include managing project plans, timelines, risks, dependencies, governance, stakeholder relationships, customer onboarding, production readiness, and cross-functional delivery. The role also provides implementation expertise, supports product launches and pilots, drives process standardization and continuous improvement, and contributes to training, mentoring, documentation, and knowledge sharing.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the long-term technical direction of the AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendation systems, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model representations, measures business impact, and partners with cross-functional stakeholders. Mentors data scientists and AI engineers, presents recommendations to leadership, contributes to hiring, and helps shape the organization’s technical direction.

Lead the design and modernization of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architect cloud-based ETL/ELT, streaming, and lakehouse solutions using Databricks, Spark, Delta Lake, and related technologies. Establish data quality, governance, lineage, security, observability, and operational standards. Provide technical leadership, mentor engineers, influence architecture and roadmaps, optimize workloads, and collaborate across product, risk, analytics, architecture, and business teams.

Lead and support customer implementations of Mastercard products and services across Europe from initiation through launch. Manage project plans, timelines, risks, dependencies, governance, stakeholder communications, and production readiness. Serve as a customer-facing implementation advisor while coordinating Product, Technology, Operations, Account Management, and regional teams. Contribute to implementation methodology improvements, standardization, documentation, training, knowledge sharing, and operational readiness.