Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together.
About The Role:
At Optum, we are reimagining health care through data, technology and innovation. We combine the power of advanced analytics, engineering and domain expertise to solve complex healthcare challenges at scale. Every day, our teams work to improve outcomes, reduce costs and create better experiences for patients, providers and consumers.
As part of a fast-paced innovation and incubation team, you will have the opportunity to work on some of the most challenging and ambiguous data problems in the organisation, helping shape future products and capabilities before they enter formal delivery.
We are seeking an experienced Senior Analytics Engineer who combines solid technical engineering capabilities with an investigative, hypothesis-driven analytical mindset. This role is ideal for someone who enjoys exploring complex datasets, identifying patterns and anomalies, validating business assumptions and transforming raw data into actionable insights. Rather than focusing solely on building production pipelines, this role sits earlier in the product lifecycle where experimentation, discovery and rapid iteration are critical to success.
You will work closely with business stakeholders, product teams, data analysts and engineering teams to evaluate new opportunities, assess feasibility and translate ambiguous requirements into evidence-based recommendations.
The successful candidate will leverage Databricks, SQL and Python to perform exploratory analysis across large and disparate enterprise datasets, producing reusable notebooks, visualisations and supporting artefacts that inform product direction and feature development.
Careers with Optum offer flexible work arrangements and individuals who live and work in the Republic of Ireland will have the opportunity to split their monthly work hours between our Dublin or Letterkenny office and telecommuting from a home-based office in a hybrid work model.
What you will do:
Data Exploration & Analysis
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Investigate large, complex and often disparate data sources to uncover trends, patterns and business opportunities
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Perform data profiling, validation and quality assessment activities
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Clean, transform and prepare datasets for exploratory and analytical use
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Identify data anomalies, inconsistencies and potential business risks
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Validate assumptions and challenge hypotheses using data-driven evidence
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Map data flow across multiple layers of the application and across separate systems
Experimentation & Discovery
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Apply an iterative test, learn and refine approach to problem solving
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Design and execute exploratory analyses to support product discovery and innovation initiatives
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Develop proof-of-concepts and analytical experiments that inform business decisions
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Translate ambiguous business questions into analytical approaches and measurable outcomes
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Support feasibility assessments for new products, features and strategic initiatives
Stakeholder Engagement
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Partner with business analysts, product managers and subject matter experts during the ideation phase of initiatives
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Facilitate conversations that help clarify requirements, assumptions and success criteria
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Present analytical findings in a manner suitable for both technical and non-technical audiences
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Provide clear recommendations supported by quantitative evidence
Analytics Engineering
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Develop maintainable SQL and Python notebooks within the Databricks ecosystem
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Create reusable analytical assets and accelerators
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Contribute to creation of semantic layer for AI enablement
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Leverage version control and engineering best practices to manage analytical code
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Contribute to the evolution of analytical and data engineering standards
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Support the transition of validated concepts and requirements into downstream engineering delivery teams
Documentation & Knowledge Sharing
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Produce well-structured notebooks that combine code, narrative explanations, assumptions, findings and recommendations
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Create visualisations and analytical artefacts that can be consumed as part of intake and feature definition processes
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Generate documentation suitable for solution design, planning and implementation teams
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Support creation of intake-ready analytical artefacts that complement business requirements and Aha! feature submissions
You will be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role, as well as providing development for other roles you may be interested in.
What you will bring:
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Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related discipline, or equivalent professional experience
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Proven extensive experience in Analytics Engineering, Data Engineering, Data Analysis, or a related discipline
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Proven experience working with enterprise-scale data warehouses, data marts, and analytical platforms
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Demonstrated advanced SQL expertise, including complex joins, window functions, aggregation strategies, and query optimization
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Demonstrated ability to utilize GitHub Actions and version control repositories
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Demonstrated solid Python proficiency, including experience using notebook-based development environments
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Proven experience working within the Databricks ecosystem
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Proven experience analyzing large and complex datasets from multiple source systems
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Proven ability to work independently with ambiguous or incomplete requirements
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Demonstrated solid verbal and written communication skills
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Proven ability to explain complex technical concepts to business stakeholders
Other useful skills and experience:
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Proven experience with Databricks Lakehouse Architecture, Delta Lake, and Unity Catalog
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Proven experience building semantic models or semantic layers
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Demonstrated familiarity with healthcare, insurance, or other highly regulated industries
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Demonstrated experience with data quality assessment and observability concepts
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Demonstrated knowledge of data modeling principles and analytical data structures
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Proven experience with Git, version control workflows, and collaborative development practices
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Demonstrated familiarity with business intelligence and data visualization tools such as Power BI
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Demonstrated exposure to machine learning, statistical analysis, or experimentation frameworks
Please note you must currently be eligible to work and remain indefinitely without any restrictions in the country to which you are making an application. Proof will be required to support your application.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
Diversity creates a healthier atmosphere: Optum is an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to gender, civil status, family status, sexual orientation, disability, religion, age, race, and membership of the Traveller community, or any other characteristic protected by law. Optum is a drug-free workplace. © 2026 Optum Services (Ireland) Limited. All rights reserved.
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