Top Tech Jobs & Startup Jobs in Dublin

Leads the design and implementation of enterprise data platforms and pipelines supporting credit risk, decisioning, analytics, regulatory reporting, and AI initiatives. Architects cloud-based lakehouse solutions using Databricks, Spark, Delta Lake, and related technologies; establishes data quality, governance, lineage, observability, and security controls; modernizes legacy systems; optimizes large-scale processing; and mentors engineers while influencing cross-functional technical strategy.

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 embeddings and foundation models, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. 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 models, recommendations, forecasting, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners across functions, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the AI organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions for forecasting, recommendations, propensity modeling, fraud detection, and customer analytics. Defines modeling and experimentation strategies, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, and mentors data scientists and AI engineers. The role also contributes to technical direction, hiring, and capability development.

Provides technical leadership as a senior individual contributor for complex, enterprise-scale software systems. Leads architecture, design, development, testing, deployment, operational readiness, and production issue resolution across distributed services and platforms. Partners with product, business, architecture, and engineering stakeholders to deliver secure, resilient, scalable solutions. Drives engineering standards, automation, CI/CD, observability, reliability, technical roadmaps, developer productivity, and technical debt reduction while mentoring engineers and influencing cross-functional initiatives.

Leads the design and delivery of enterprise data platforms and pipelines supporting credit risk, decisioning, analytics, regulatory reporting, and AI initiatives. Architects cloud-based lakehouse solutions using Databricks, Spark, Delta Lake, and modern ETL/ELT patterns. Establishes data quality, governance, lineage, observability, security, and compliance capabilities; modernizes legacy platforms; optimizes large-scale workloads; and drives engineering standards. Partners cross-functionally, influences architecture and roadmaps, mentors engineers, resolves complex dependencies, and supports technical hiring.

Leads enterprise-scale software engineering as a senior individual contributor and technical thought leader. Designs resilient, secure, scalable systems; drives architecture, development, testing, deployment, automation, observability, and operational excellence. Partners across product, business, architecture, and engineering teams, resolves complex production issues, reduces technical debt, improves engineering practices, and influences technology roadmaps. Mentors engineers and contributes to architecture forums, technical communities, and global engineering standards.

Leads architecture, design, development, modernization, and delivery of scalable cloud-native experimentation and analytics software. Builds services, APIs, data pipelines, and analytical capabilities using AWS, Azure, Databricks, Spark, and PySpark. Provides technical leadership across distributed teams, drives design and code reviews, mentors engineers, and champions security, reliability, observability, performance, and continuous delivery.

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, metrics, and technical direction while partnering with business, product, engineering, and analytics teams. Presents insights to senior stakeholders, mentors data scientists and AI engineers, and drives projects from problem definition through measurable business impact and production deployment.

Lead architecture and hands-on development of Mastercard’s cloud-native experimentation and analytics platform. Design scalable services, APIs, data pipelines, and distributed systems using AWS, Azure, Databricks, and Spark/PySpark. Drive modernization, technical strategy, design reviews, delivery across global teams, and engineering best practices for security, reliability, observability, and performance. Mentor engineers and collaborate with product, data science, QA, security, and operations teams.