Top Tech Jobs & Startup Jobs in Dublin

Leads enterprise business intelligence and reporting for Optum Health Performance Management. Designs dashboards, scorecards, data models, reporting pipelines, visualization frameworks, and automated reporting processes. Ensures data quality, governance, documentation, lineage, and timely delivery of executive, provider, market, operational, and performance reports. Translates business requirements into scalable reporting solutions and collaborates with analytics, technology, and data engineering teams on reporting modernization.

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.

Provides strategic and operational leadership for a Provider Growth analytics portfolio. Defines analytics strategy, leads multidisciplinary teams, owns analytics products, and drives AI and machine learning adoption. Develops solutions for provider targeting, segmentation, market prioritization, campaign optimization, and growth opportunities. Partners with executives and technical teams, manages roadmaps, budgets, governance, delivery quality, talent development, and enterprise-scale data and AI capabilities.

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.

Leads complex, strategic projects from initiation through implementation for Payment Integrity’s transformation agenda. Defines scope, milestones, governance, metrics, and execution plans; coordinates cross-functional dependencies; manages risks and roadblocks; aligns stakeholders; supports executive decision-making through clear reporting; and improves project delivery processes. The role partners across operations, technology, product, finance, compliance, and strategy, while leveraging AI and digital automation to improve execution and business outcomes.

Lead complex, cross-functional Payment Integrity transformation projects from initiation through implementation. Define scope, milestones, governance, metrics, and execution strategies; manage dependencies, risks, stakeholders, and competing priorities; remove roadblocks; and drive accountability. Prepare executive communications and reporting, facilitate decisions, resolve conflicts, and improve project delivery practices. Use AI and digital automation to streamline execution and enhance business outcomes.

Leads end-to-end software engineering for analytics platforms and applications, including architecture, development, testing, deployment, support, and technical direction. Builds scalable AI-powered solutions and large-scale data pipelines with Python, PySpark, and SQL. Evaluates emerging AI tools, maintains GitHub Actions CI/CD, supports cloud development, conducts reviews, creates prototypes, documents systems, and partners with product, architecture, data science, and engineering teams.

Leads data scientists, analysts, and engineers integrating pricing models into an enterprise pharmacy pricing platform. Provides technical leadership across solution design, platform integration, production delivery, analytics architecture, and software engineering. Manages resources, coaches team members, partners with product, engineering, and business leaders, drives continuous improvement, and communicates analytical results and predictive models. The role requires Python and SQL expertise, people management, enterprise production delivery, financial modeling, and Agile experience.

Designs and operationalizes data products supporting analytics, machine learning, generative AI, and agentic AI use cases. The role models and transforms healthcare data, analyzes trends, ensures data quality, supports risk adjustment and customer targeting, and collaborates with data scientists and AI engineers to evaluate models and improve business adoption.

Design, deploy, and operate production AI agents and generative AI solutions using Azure OpenAI, Snowflake, Databricks, retrieval, semantic models, and tool orchestration. Build reliable data workflows, governance, security, monitoring, evaluation, and responsible AI controls for sensitive healthcare data. Integrate AI systems with enterprise applications and APIs, troubleshoot performance and retrieval issues, and collaborate with technical and business stakeholders to deliver compliant, scalable solutions.