Top Python Jobs in Dublin

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.

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.

Monitor and respond to production alerts, troubleshoot distributed applications, improve reliability, and reduce recovery time. Support deployments and CI/CD pipelines across environments, automate operational processes, analyze ITSM activities, and improve service availability, latency, and system health. Collaborate globally across development, operations, and product teams, participate in incident response and blameless postmortems, mentor junior staff, and promote DevOps standards and best practices.

Leads the design and modernization of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI. Architects Databricks, Spark, Delta Lake, and cloud-based solutions; establishes governance, quality, lineage, observability, and security controls; optimizes large-scale processing; and guides technical strategy. Partners across risk, product, architecture, and engineering, mentors teams, influences stakeholders, supports compliance, and drives delivery across complex initiatives.

Monitor and respond to production alerts, troubleshoot distributed applications, support deployments and CI/CD pipelines, and improve service reliability through automation. The role maintains system health, participates in incident response and blameless postmortems, analyzes ITSM activities, and partners with development, operations, and product teams to improve resiliency, operational efficiency, and deployment velocity.

Monitor and respond to production alerts, troubleshoot distributed applications, improve system reliability, and reduce recovery time. Support service lifecycle management, incident response, postmortems, CI/CD pipelines, deployments, and operational gating. Automate routine processes, analyze ITSM activities, identify resiliency gaps, and collaborate with development, operations, and product teams to advance DevOps standards and practices.

Leads the design and modernization of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architects cloud-based lakehouse solutions using Databricks, Spark, Delta Lake, and related technologies; establishes governance, quality, lineage, observability, security, and compliance controls; optimizes large-scale workloads; and drives technical standards, cross-functional delivery, mentoring, and strategic roadmap planning.

Leads the design and modernization of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Builds scalable cloud-based ETL/ELT and streaming solutions using Databricks, Spark, Delta Lake, SQL, and Python. Establishes data quality, governance, lineage, security, monitoring, and operational excellence practices. Partners across risk, product, architecture, and engineering; influences technical direction, mentors engineers, supports compliance, and drives strategic roadmap execution.

Monitor and respond to production alerts, troubleshoot distributed applications, improve reliability and mean time to recovery, and support service operations. Build and enhance CI/CD pipelines, automate manual processes, validate deployments, and establish DevOps best practices. Analyze ITSM activities, monitor system health, participate in incident response and blameless postmortems, collaborate across global technology teams, and mentor junior staff.

Lead machine learning and data science initiatives from problem definition through production deployment and business impact measurement. Develop predictive models, recommendation systems, forecasting, fraud detection, and customer analytics solutions using modern machine learning and foundation-model techniques. Establish experimentation and evaluation frameworks, partner with cross-functional stakeholders, present technical recommendations, mentor data scientists and AI engineers, and shape the organization’s technical direction.

Monitor and respond to production alerts, troubleshoot distributed applications, support deployments and CI/CD pipelines, automate operational processes, improve system reliability, and participate in incident response and blameless postmortems. The role also measures service health, collaborates with global development and operations teams, provides operational feedback, and mentors junior colleagues while advancing DevOps practices.

Leads the design and implementation of enterprise data platforms, ETL/ELT pipelines, lakehouse architectures, and distributed processing systems supporting credit risk and analytics. Establishes data quality, governance, lineage, security, monitoring, and operational standards while modernizing legacy assets in the cloud. Partners with product, risk, architecture, and data science teams, mentors engineers, influences technical strategy, optimizes performance and cost, supports compliance, and drives complex cross-functional initiatives.

Monitor and respond to production alerts, troubleshoot distributed web applications, improve reliability, and reduce recovery time. Support application deployments and CI/CD pipelines across environments, automate operational processes, analyze ITSM activities, and identify resiliency gaps. Collaborate with global development, operations, and product teams, participate in incident response and blameless postmortems, maintain service health metrics, and mentor junior team members while advancing DevOps practices.

Monitor and respond to production alerts, troubleshoot distributed applications, improve reliability and system health, support CI/CD pipelines and deployments, automate operational processes, conduct incident response and blameless postmortems, and collaborate with development, operations, and product teams on DevOps best practices.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendations, fraud detection, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, drives projects from conception through production, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. Contributes to hiring, capability development, and the organization’s long-term technical direction.

Lead the design and evolution of enterprise data platforms and pipelines supporting credit risk, decisioning, regulatory reporting, analytics, and AI initiatives. Architect cloud-based ETL and ELT solutions using Databricks, Spark, Delta Lake, and related technologies. Establish data quality, governance, lineage, observability, security, and compliance controls. Drive modernization, performance optimization, technical standards, cross-functional delivery, architectural decisions, mentoring, talent assessment, and strategic roadmap planning.

Leads the design, development, and modernization of enterprise data platforms and pipelines supporting credit risk, analytics, regulatory reporting, and AI initiatives. Architects cloud-based ETL/ELT and streaming solutions using Databricks, Spark, Delta Lake, and related technologies. Establishes data quality, governance, lineage, security, monitoring, and operational standards while optimizing performance and cost. Partners with cross-functional stakeholders, influences architecture and roadmap decisions, mentors engineers, and drives delivery across complex initiatives.

Leads the design, development, deployment, and evaluation of advanced machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies embeddings and foundation-model techniques, measures business impact, and partners with business, product, engineering, and analytics teams. Mentors data scientists and AI engineers, influences technical direction, presents findings to leadership, and contributes to hiring and capability development.

Design, build, test, and maintain scalable data engineering solutions, including automated releases, ETL processes, data models, real-time pipelines, monitoring, legacy migrations, and security strategies. Transform raw data using business logic, support machine learning and business intelligence workloads, and produce technical documentation. The role requires extensive experience with cloud platforms, SQL, databases, data warehousing, Spark, Databricks, Airflow, Kubernetes, Docker, Python, and related data technologies.

Supports secure software development by executing security solutions, writing secure code, analyzing incident and vulnerability data, validating AI-assisted recommendations, and contributing to security testing, resiliency, continuity training, and control validation. The role requires knowledge of software development lifecycles, network and information security, IT risk, cloud technologies, and architectural concepts.

Build and maintain scalable ETL pipelines, integrate data from databases, APIs, streaming platforms, and external providers, and transform large datasets for analytics and machine learning. Establish reusable engineering frameworks, data governance, monitoring, alerting, and reliability practices. Collaborate with analytics and business teams on cloud data migration, predictive model enablement, and healthcare cost reduction. Required skills include SQL, Python, Scala or Java, cloud platforms, Snowflake or Databricks, DevOps, Git, and CI/CD.

Designs and delivers secure, scalable Open Banking services; remains hands-on in coding, architecture reviews, and technical design. Partners with product and business teams, leads architectural decisions, mentors engineers, conducts code reviews and interviews, and drives enterprise-wide technical alignment. Requires expertise in Java-based technologies, microservices, cloud environments, secure development, cryptography, compliance, and vulnerability management within financial services.

Own end-to-end quality engineering for agentic applications, APIs, user interfaces, distributed systems, and platform services. Design automation frameworks, define AI and agent testing strategies, build CI/CD quality gates, validate performance and resilience, analyze defects, and drive root-cause resolution. Collaborate with engineering, product, architecture, and AI teams to embed quality throughout development. Improve testability and release confidence while mentoring teammates on automation and quality practices.

Own end-to-end quality engineering for AI and agentic applications, APIs, user interfaces, distributed systems, and platform services. Design automation frameworks, define AI testing strategies, integrate quality gates into CI/CD pipelines, and evaluate performance, resilience, reliability, and scalability. Partner with engineering, product, architecture, and AI teams to resolve defects, improve testability, mentor colleagues, and strengthen release confidence.