Top Tech Jobs & Startup Jobs in Dublin

Own product workstreams for Mastercard’s Test & Learn experimentation platform, using customer research, market insights, usage data, and stakeholder feedback to guide roadmap decisions. Partner with engineering, design, sales, marketing, and regional teams to deliver capabilities, support adoption, and improve go-to-market readiness. Identify AI opportunities, advise market-facing teams on product direction, contribute to positioning and launch plans, and mentor junior product professionals.

Lead system design and develop scalable, cloud-native software for a data-intensive business experimentation platform. Build distributed services, APIs, analytics capabilities, and data pipelines using Java, Databricks, Spark, and modern cloud technologies. Improve performance, reliability, security, observability, testing, and CI/CD practices. Troubleshoot complex production issues, collaborate across teams, and mentor engineers throughout the software development lifecycle.

Leads major software engineering initiatives, defines technical strategy and roadmaps, evaluates technologies through proofs of concept, and guides cross-functional teams. Oversees project scope, integration architecture, security, development standards, documentation, and service-level requirements. Partners with business, legal, compliance, vendors, and senior leadership on business cases, third-party integrations, and strategic decisions. Mentors engineers and supports development, testing, and operations for global, multilingual, multicurrency systems.

Own product workstreams for Mastercard’s Test & Learn experimentation platform, using customer research, market insights, analytics, and stakeholder feedback to guide roadmap decisions. Partner with engineering, design, sales, marketing, and regional teams to deliver capabilities, support adoption, and prepare launches. Help identify AI opportunities, provide product guidance, define positioning and enablement materials, and mentor junior product team members.

Design and develop scalable, cloud-native experimentation platforms and data-intensive analytics applications. Lead team-level system design, APIs, data flows, and nonfunctional requirements while coding, testing, debugging, and optimizing production software. Build distributed systems, microservices, and data pipelines using Java, Databricks, Spark, and cloud technologies. Troubleshoot complex issues, improve reliability and observability, collaborate cross-functionally, and mentor engineers.

Own product workstreams for Mastercard’s Test & Learn experimentation platform, using customer research, market insights, analytics, and stakeholder feedback to shape roadmap decisions. Partner with engineering, design, sales, marketing, and regional teams to deliver scalable capabilities, improve go-to-market readiness, and drive adoption. Identify AI opportunities, support product positioning and launches, advise market-facing teams, and mentor junior product professionals.

Leads the planning, architecture, design, and delivery of scalable, secure software solutions for global customers. Drives AI and emerging technology initiatives from research through production, champions automation across the software lifecycle, and collaborates with engineering, data, product, operations, and customer teams. Provides technical leadership for customer integrations, improves platform performance and reliability, and ensures solutions align with enterprise standards and business objectives.

Designs, develops, tests, and supports scalable, cloud-native experimentation platforms and analytics-driven applications. Responsibilities include leading team-level system design, building distributed services and APIs, optimizing Databricks and Spark workloads, troubleshooting performance and reliability issues, and translating business needs into secure technical solutions. The engineer collaborates across teams, contributes throughout the software lifecycle, improves CI/CD and observability practices, and mentors junior and mid-level engineers.

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.