Data Modeller – Healthcare Domain
Job Summary
Job Description
We are seeking an experienced Data Modeller with expertise in designing and implementing data models for modern data platforms, specifically within the healthcare domain. This role involves deep knowledge of data modeling techniques, healthcare data structures, and experience with Databricks Lakehouse architecture. The ideal candidate will translate complex business requirements into efficient, scalable data models that support analytics and reporting needs, ensuring data integrity, performance, and compliance with healthcare industry standards. Responsibilities include designing and implementing logical and physical data models for Databricks Lakehouse, creating data dictionaries, developing dimensional and data vault models, and supporting migration from legacy systems.
Must have:
- Data modeling for analytics
- Dimensional/Data vault modeling
- Databricks/Delta Lake experience
- Healthcare data modeling expertise
- Legacy to modern platform migration
- Strong SQL skills
- Data governance understanding
- Healthcare data structures
- Healthcare terminology/coding
- Healthcare data standards
Good to have:
- Data modeling tools experience
- Performance optimization
- Cloud platform knowledge
- Big data technologies
- Clinical/operational modeling
- Population health data needs
- Advanced degree
- Professional certifications
Perks:
- Opportunity to design cutting-edge healthcare analytics models
- Collaborative and innovative work environment
- Competitive compensation package
- Professional development opportunities
- Work with leading data technologies
7 skills required
Job Details
Overview
We are seeking an experienced Data Modeller with expertise in designing and implementing data models for modern data platforms. This role requires deep knowledge of data modeling techniques, healthcare data structures, and experience with Databricks Lakehouse architecture. The ideal candidate will have a proven track record of translating complex business requirements into efficient, scalable data models that support analytics and reporting needs.
About the Role
As a Data Modeller, you will be responsible for designing and implementing data models for our Databricks-based Modern Data Platform. You will work closely with business stakeholders, data architects, and data engineers to create logical and physical data models that support the migration from legacy systems to the Databricks Lakehouse architecture, ensuring data integrity, performance, and compliance with healthcare industry standards.
Key Responsibilities
Qualifications
Technical Skills
Personal Attributes
What We Offer
- Design and implement logical and physical data models for Databricks Lakehouse implementations
- Translate business requirements into efficient, scalable data models
- Create and maintain data dictionaries, entity relationship diagrams, and model documentation
- Develop dimensional models, data vault models, and other modeling approaches as appropriate
- Support the migration of data models from legacy systems to Databricks platform
- Collaborate with data architects to ensure alignment with overall data architecture
- Work with data engineers to implement and optimize data models
- Ensure data models comply with healthcare industry regulations and standards
- Implement data modeling best practices and standards
- Provide guidance on data modeling approaches and techniques
- Participate in data governance initiatives and data quality assessments
- Stay current with evolving data modeling techniques and industry trends
- Extensive experience in data modeling for analytics and reporting systems
- Strong knowledge of dimensional modeling, data vault, and other modeling methodologies
- Experience with Databricks platform and Delta Lake architecture
- Expertise in healthcare data modeling and industry standards
- Experience migrating data models from legacy systems to modern platforms
- Strong SQL skills and experience with data definition languages
- Understanding of data governance principles and practices
- Experience with data modeling tools and technologies
- Knowledge of performance optimization techniques for data models
- Bachelor's degree in Computer Science, Information Systems, or related field; advanced degree preferred
- Professional certifications in data modeling or related areas
- Data modeling methodologies (dimensional, data vault, etc.)
- Databricks platform and Delta Lake
- SQL and data definition languages
- Data modeling tools (erwin, ER/Studio, etc.)
- Data warehousing concepts and principles
- ETL/ELT processes and data integration
- Performance tuning for data models
- Metadata management and data cataloging
- Cloud platforms (AWS, Azure, GCP)
- Big data technologies and distributed computing
- Healthcare data structures and relationships
- Healthcare terminology and coding systems (ICD, CPT, SNOMED, etc.)
- Healthcare data standards (HL7, FHIR, etc.)
- Healthcare analytics use cases and requirements
- Optionally Healthcare regulatory requirements (HIPAA, HITECH, etc.)
- Clinical and operational data modeling challenges
- Population health and value-based care data needs
- Strong analytical and problem-solving skills
- Excellent attention to detail and data quality focus
- Ability to translate complex business requirements into technical solutions
- Effective communication skills with both technical and non-technical stakeholders
- Collaborative approach to working with cross-functional teams
- Self-motivated with ability to work independently
- Continuous learner who stays current with industry trends
- Opportunity to design data models for cutting-edge healthcare analytics
- Collaborative and innovative work environment
- Competitive compensation package
- Professional development opportunities
- Work with leading technologies in the data space
This position requires a unique combination of data modeling expertise, technical knowledge, and healthcare industry understanding. The ideal candidate will have demonstrated success in designing efficient, scalable data models and a passion for creating data structures that enable powerful analytics and insights.
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