Data Analyst, Network Pricing & Healthcare Analytics

Optum; Dublin; On-site; EUR 80,000 - 100,000; Full time

Benefits offered by this job

Hybrid work model

Career development opportunities

Diversity and inclusion culture

Job summary

Optum Ireland is seeking a data engineer to join the Pharmacy Reimbursement Analytics team in a full-time, on-site role in Dublin. You will build and maintain data pipelines, validate data quality, and develop analytics datasets to support network pricing and financial reporting.

You will collaborate with Analytics and Enterprise Data Engineering teams, work on large healthcare datasets, and contribute to automation and AI-enabled analytics in a diverse, inclusive environment.

Qualifications

• Bachelor's degree or higher in analytics, CS, engineering, finance, or related field.
• Proven experience with SQL, Databricks, Python on large datasets.
• Advanced proficiency in Microsoft Excel.
• Experience building and validating analytical datasets and pipelines.
• Ability to translate complex data into actionable business insights.
• Attention to data quality, governance, and controls.

Responsibilities

• Manage, maintain, and enhance data pipelines for pharmacy reimbursement analytics, pricing, and financial reporting.
• Develop and support analytical datasets for modelling and performance measurement.
• Perform data validation, quality assurance, and governance activities.

Skills

SQL

Databricks

Python

Excel

Data pipelines

Data governance

Data validation

Stakeholder communication

Cloud platforms

Analytics

Education

Bachelors degree

Tools

Databricks

SQL databases

Python

Job description

Optum Ireland is seeking a data engineer to join the Pharmacy Reimbursement Analytics team in a full-time, on-site role in Dublin. You will build and maintain data pipelines, validate data quality, and develop analytics datasets to support network pricing and financial reporting.

You will collaborate with Analytics and Enterprise Data Engineering teams, work on large healthcare datasets, and contribute to automation and AI-enabled analytics in a diverse, inclusive environment.