Senior Data Modeler

Requirements

• Dimensional modeling using Kimball methodology (star and snowflake schemas, fact and dimension tables, SCDs)Must
• Healthcare industry experience with Encounters dataMust
• Experience with claims, member, or provider data in healthcare payer or provider settingsMust
• Advanced SQL skills including complex query writing, performance tuning, and debuggingMust
• Data profiling and quality checks across large datasetsMust
• Design logical and physical data models for data warehouses and lakehousesMust
• Problem-solving and attention to detailMust
• Cross-functional collaboration and technical leadership with data engineers, BI teams, and business stakeholdersMust
• Consultancy mindset and solution-oriented approachMust

What you'll do

• Design and maintain dimensional data models
• Model healthcare Encounters data ensuring accuracy and regulatory compliance
• Develop and optimize complex SQL queries for extraction, transformation, and validation
• Perform data profiling, quality checks, gap analysis, and troubleshooting
• Collaborate with data engineering teams to implement models in data warehouse or lakehouse environment
• Maintain data dictionaries and mapping specifications
• Partner with BI and analytics teams to ensure models support reporting needs

Keywords

About the role

Our partner, a Fortune 500 company , is building scalable, analytics-ready data architectures for a client in the healthcare sector. We're looking for a Senior Data Modeller to design and maintain dimensional data models using Kimball methodology that power reporting and analytics at scale. You'll translate business requirements into well-structured logical and physical models, working closely with data engineers, BI teams, and business stakeholders — with particular emphasis on healthcare Encounters data. This is a long-term, remote-first contract position with required US working hours overlap (2-6 PM CET). Responsibilities • Dimensional modeling: design and maintain data models using Kimball methodology (star and snowflake schemas, fact and dimension tables, SCDs). • Healthcare Encounters data: model Encounters data, ensuring accuracy and alignment with business and regulatory requirements. • Advanced SQL: develop and optimize complex queries for data extraction, transformation, and validation. • Implementation: collaborate with data engineering teams to implement models within the data warehouse/lakehouse environment. • Data quality: perform data profiling, quality checks, gap analysis, and troubleshooting across source and target systems. • Documentation: maintain data models, data dictionaries, and mapping specifications. • BI enablement: partner with BI and analytics teams to ensure models support downstream reporting needs. Work Conditions • Type: Full-time & Long-term contract work • Start Date : ASAP • Location : Remote • US Time Zone Overlap : Required ( 2 PM - 6 PM CET , ideally until 7 PM CET) • Contract with EU LLC Requirements • Healthcare industry experience — including hands-on knowledge of Encounters data. • Experience working with claims, member, or provider data in a healthcare payer (health insurer) or provider setting. • Strong Kimball dimensional modeling background — star/snowflake schemas, fact and dimension tables, slowly changing dimensions (SCDs). • Advanced SQL skills — complex query writing, performance tuning, debugging, and data profiling across large datasets. • Proven ability to design logical and physical data models for data warehouses/lakehouses optimized for reporting and analytics. • Excellent problem-solving skills and keen attention to detail. • Ability to collaborate with cross-functional teams and lead technical discussions with data engineers, BI teams, and business stakeholders. • Have a consultancy mindset → always try to find a solution for the client Highlights If you are passionate about Data Modeling , SQL , Healthcare data , and building analytics-ready data warehouses , this role with our client offers an exciting opportunity to shape healthcare analytics! Originally posted on Himalayas