Headquartered in Dublin, Ohio, Cardinal Health, Inc. (NYSE: CAH) is a global, integrated healthcare services and products company, providing customized solutions for hospitals, health systems, pharmacies, ambulatory surgery centers, clinical laboratories and physician offices worldwide.
The company provides clinically proven medical products and pharmaceuticals and cost-effective solutions that enhance supply chain efficiency from hospital to home. Cardinal Health connects patients, providers, payers, pharmacists and manufacturers for integrated care coordination and better patient management. Backed by nearly 100 years of experience, with approximately 50,000 employees in 46 countries, Cardinal Health ranks among the top 20 on the Fortune 500.
Department Overview:
At Navista Advanced Analytics, our mission is to empower community oncology practices to deliver patient-centered cancer care. Navista, a Cardinal Health company, is an oncology practice alliance co-created with oncologists and practice leaders that offers advanced support services and technology to help practices remain independent and thrive.
Job Overview:
As a Senior Data Engineer, you will involve in analyzing comprehensive patient data to gain insights for improved care, research, and operations. This includes working with various data sources, including electronic health records (EHR), claims data, and patient-reported data, to identify trends, predict outcomes, and support decision-making.
You will help define and implement multi-cloud-based infrastructure for Data Analytics and Machine Learning initiatives. In this critical role, primary focus is to architect, implement and operationalize large-scale enterprise data solutions leveraging one or more of Google Cloud Platform technologies like BigQuery, Cloud Dataflow, Google Health Care Data Engine (HDE) and Looker. As a primary subject matter expert, you will be implementing and providing consultation services.
Responsibilities:
- Data Collection and Transformation: Gather data from diverse sources like EHRs, claims databases, and patient surveys.
- Data Warehousing: Lead the design and implementation of data warehousing systems for Patient 360 initiatives.
- Data Modeling: Define data models, business rules, and quality criteria for Patient 360.
- Analytics and Reporting: Develop analytical capabilities and generate reports to support decision-making and research.
- Data Privacy: Collaborate with data privacy teams to ensure compliance with regulations like HIPAA.
- Statistical Analysis: Conduct statistical analysis and predictive modeling to identify trends and patterns.
- Hands-On Experience: Creating datasets for Machine learning algorithms and data analysis. Design and build low-code/no-code data pipeline frameworks to support large scale ingestions and practice integrations. Optimize data pipelines for cost optimized large scale data lake implementations.
- Data Architecture Design: Designing and implementing Data model, Data architecture for patient 360 deg applications and Common Data Services using cloud native integration and analytics technologies.
- Technical Leadership: Provide technical guidance to data engineering teams, mentoring junior engineers on best practices for data pipeline development, data modeling, and performance optimization. Assist with integration practice integration engines to the data infrastructure.
- Collaboration: Work closely and collaboratively with other members of the analytics teams including data scientists, data engineers, business analysts, and product teams to define requirements, mine and analyze data, integrate data from a variety of sources.
Desired Qualifications:
- Bachelor’s degree in engineering and equivalent education experience.
- 10+ years of experience in Data Analytics, with at least 2+ years of experience working with healthcare data.
- Prior Experience of EMR/Clinical databases and Oncology or other community Disease practices - Good to have.
- Prior experience of working with Healthcare interoperability Integration engines and Fast Healthcare Interoperability Resources (FHIR) data.
- Multi cloud Experience – Google Cloud Preferred.
- Strong Data modeling experience in Modern cloud DWH like Big Query and Lakehouse like Databricks.
- Experience with data analytics tools like Looker and Tableau - Good to have.
- Architecting and designing data lakes on GCP cloud analytics, BI and Machine learning workloads
- Writing complex SQL queries, stored procedures, etc.
- Prior experience working in an Agile team.
- CI/CD pipelines such as Concourse, Jenkins.
Candidates who are back-to-work, people with disabilities, without a college degree, and Veterans are encouraged to apply.
Cardinal Health supports an inclusive workplace that values diversity of thought, experience and background. We celebrate the power of our differences to create better solutions for our customers by ensuring employees can be their authentic selves each day. Cardinal Health is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ancestry, age, physical or mental disability, sex, sexual orientation, gender identity/expression, pregnancy, veteran status, marital status, creed, status with regard to public assistance, genetic status or any other status protected by federal, state or local law.
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