Senior Financial Data & Analytics Engineer
Role details
Job location
Tech stack
Job description
- Data Engineering & Integration Architecture:
- Design and implement a centralized financial data warehouse integrating PeopleSoft, HR, CPMP, Report Center, SOMDASH, and external data sources.
- Develop and maintain ETL/ELT pipelines for structured and semi-structured data.
- Build and manage API-based data ingestion pipelines.
- Ensure scalability, performance, and reliability of data architecture.
- Collaborate with IT and enterprise data teams on infrastructure and platform designs.
- Advanced Financial & Clinical Analyst:
- Develop analytics models for physician productivity (wRVUs), reimbursement, and compensation.
- Apply benchmarking data (e.g. Vizient) to comparative performance analysis.
- Build predictive and trend models to support financial planning.
- Analyze payer mix, revenue cycles, and cost structures across departments.
- Data Modeling & Financial Intelligence:
- Design data models supporting funds flow, ROI analysis, and All-Funds financial reporting.
- Develop multi-dimensional datasets integrating clinical, academic, and financial data.
- Create standardized metrics and definitions for institutional reporting.
- Support scenario modeling and financial forecasting.
- Business Intelligence & Data Visualization
- Develop and maintain executive-level dashboards using Tableau or equivalent tools.
- Build self-service analytics tools for departments and leadership.
- Design intuitive, scalable, and interactive reporting solutions.
- Translate complex datasets into actionable insights.
- Data Governance, Quality, & Collaboration:
- Establish and enforce data quality, validation, and reconciliation processes.
- Support data governance frameworks and compliance with institutional policies.
- Collaborate with SOM Finance, Clinical Practice. HR, IT and leadership stakeholders.
- Present findings and recommendations to executive leadership.
- Perform other duties and special projects assigned in support of departmental and institutional research missions.
Requirements
Bachelor's degree (foreign equivalent of higher) in Data Science, Computer Science, Information Systems, Finance, Economics, or related field. Five (5) years or more of full-time experience in data engineering, data analytics, or financial analytics in a healthcare or enterprise environment. Experience working with SQL, and relational database systems, data warehouse design, (e.g. dimensional modeling, star schema) ETL/ELT pipeline development, API integration and data ingestion, Tableau or equivalent BI platforms. Experience integrating data across ERP systems (e.g. PeopleSoft), HR systems, and operational/clinical datasets. Knowledge of physician productivity metrics (e.g. wRVUs) and healthcare financial data structures., Master's degree (foreign equivalent or higher) in Data Science, Analytics, Health Informatics, Finance, or related field. Experience with modern data stack technologies (e.g. Snowflake, Databricks, Azure/AWS data services). Experience working with Python, R, or similar programming languages for analytics or automation. Familiarity with benchmarking datasets (e.g. Vizient, MGMA, AAMC). Experience working in academic medical centers of healthcare system environments. Knowledge of data governance, HIPPA, and secure data architecture practices. Experience working with financial statements, budgeting, forecasting, and accounting principles. Experience using AI assisted analytic platforms or features within tools such as Tableau Power BI or Excel., The Senior Financial Data & Analytics Engineer designs, develops, and maintains enterprise financial data infrastructure and analytics solutions for the School of Medicine. This includes building data pipelines, integrating enterprise systems, developing predicative and descriptive analytics, and delivering executive-level dashboards. The incumbent operates under general direction and exercises significant independent judgement in architecting scalable, secure, and high-performance analytic solutions that support institutional financial strategy. The ideal applicant will have strong analytical, programming, and problem-solving skills. In the performance of all job duties, at all times be responsible for delivering optimal customer service, protecting institutional data and privacy, and ensuring the excellent delivery of solutions and services by following divisional and University policies, procedures, and processes.