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Shriners Children's

US - Analytics Engineer

Posted Yesterday
Remote
Hiring Remotely in United States
Mid level
Remote
Hiring Remotely in United States
Mid level
Designs and maintains healthcare data transformation workflows, semantic models, data marts, reports, and dashboards using PySpark, SQL, DAX, and Power BI. Integrates FHIR, HL7, and OMOP data while supporting governance, data quality, lineage, HIPAA compliance, and secure data handling. Collaborates with analysts, data scientists, and clinical and operational stakeholders to deliver reliable analytics-ready data and enable AI and predictive analytics initiatives.
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Company Overview


Shriners Children’s is an organization that respects, supports, and values each other. Named as the 2025 best mid-sized employer by Forbes, we are engaged in providing excellence in patient care, embracing multi-disciplinary education, and research with global impact. We foster a learning environment that values evidenced based practice, experience, innovation, and critical thinking. Our compassion, integrity, accountability, and resilience define us as leaders in pediatric specialty care for our children and their families.


With 20+ hospitals, outpatient clinics, ambulatory care centers and outreach locations across the globe, we provide excellent care to children up to age 18 regardless of their family’s ability to pay or insurance status. Please click here to learn more about our locations.


CURRENT EMPLOYEES: Please log into Workday Click Here to apply internally through the "Jobs Hub"


Job Description


The Analytics Engineer plays a key role in designing, building, and maintaining the data assets that power analytics, reporting, and AI-driven initiatives across the organization. This individual bridges data engineering and business intelligence—transforming raw healthcare data into trusted, analytics-ready models and scalable insights. The ideal candidate will be fluent in PySpark, SQL, and modern data modeling techniques, with a strong understanding of healthcare data standards and the analytical needs of clinical and operational stakeholders.

Key Responsibilities

  • Develop and optimize data transformation workflows in PySpark and SQL to prepare data for analytics and reporting.

  • Design, maintain, and document semantic models and data marts in alignment with enterprise data architecture (e.g., medallion or layered lakehouse design).

  • Collaborate with data governance and quality teams to ensure adherence to standards, lineage, and DQA processes.

  • Automate and orchestrate data refresh processes for analytics environments.

  • Build efficient and reusable data models to support Power BI and AI/ML use cases.

  • Partner with analysts, data scientists, and business leaders to ensure reliable access to curated, high-quality data.

  • Build and maintain enterprise reports and dashboard including measures, KPIs, and business logic that populates them.

  • Work with FHIR, HL7, and other healthcare data standards to harmonize and integrate data across systems.

  • Implement best practices for HIPAA compliance, privacy, and secure data handling within all analytics workflows.

  • Contribute to the modernization of analytics infrastructure, enabling AI and predictive analytics readiness.

  • Explore and prototype new tools or frameworks to improve efficiency, reliability, or insight delivery.

Required Qualifications:

  • Bachelor’s degree in Data Science, Computer Science, Healthcare Informatics

  • 3+ years of experience in data engineering, analytics development, or BI engineering (healthcare experience preferred).

  • Proficiency in PySpark, SQL, and DAX for data preparation and transformation.

  • Experience with Power BI or similar BI tools for semantic modeling and visualization.

  • Understanding of healthcare data standards (FHIR, HL7, OMOP) and compliance frameworks (HIPAA).

  • Experience working in Agile or DevOps environments.

Preferred Qualifications

  • Familiarity with modern data platforms such as Microsoft Fabric, Databricks, or Azure Synapse.

  • Experience integrating analytics workflows with AI/ML solutions.

  • Knowledge of version control, CI/CD, and environment-based deployment practices.

  • Advanced degree in Data Science, Computer Science, Healthcare Informatics, or related field

Compensation is determined based on years of relevant experience and departmental equity.

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